Perceptual bias reveals slow-updating in autism and fast-forgetting in dyslexia

What you saw a while ago determines what you see now: Extending awareness priming to implicit behaviors and uncovering its temporal dynamics

Past experiences influence how we perceive and respond to the present. A striking example is awareness priming, in which prior conscious perception enhances visibility and discrimination of subsequent stimuli. In this partially pre-registered study, we address a long-standing debate and broaden the scope of awareness priming by demonstrating its effects on implicit motor responses. Using a large sample size (N = 48) and a novel continuous flash suppression (CFS) paradigm, we show that prior conscious perception not only boosts subjective visibility, objective discrimination accuracy, but also enhances implicit motor responses of subsequently encountered threshold-level stimuli. Exploratory temporal dynamics analyses confirm the transient nature of awareness priming: It peaks rapidly and decays gradually, even when high-visibility trials, which could shape subsequent perception, persist. This temporal profile sets awareness priming apart from other influences of prior experience, such as serial dependence or perceptual learning. We also make a novel observation: Recent conscious experience enhances discrimination accuracy, whereas more distant experiences primarily improve subjective visibility. These findings suggest that prior conscious perception shapes conscious awareness and discrimination accuracy through independent mechanisms, likely mediated by brain areas with differing temporal receptive windows across the cortical hierarchy. By shedding new light on the scope and temporal dynamics of awareness priming, this work advances our understanding of how previous conscious perception shapes current perception and behavior.

Intact Serial Dependence in Schizophrenia: Evidence from an Orientation Adjustment Task

BACKGROUND AND HYPOTHESIS

For a long time, it was proposed that schizophrenia (SCZ) patients rely more on sensory input and less on prior information, potentially leading to reduced serial dependence-ie, a reduced influence of prior stimuli in perceptual tasks. However, existing evidence is constrained to a few paradigms, and whether reduced serial dependence reflects a general characteristic of the disease remains unclear.

STUDY DESIGN

We investigated serial dependence in 26 SCZ patients and 27 healthy controls (CNT) to evaluate the influence of prior stimuli in a classic visual orientation adjustment task, a paradigm not previously tested in this context.

STUDY RESULTS

As expected, the CNT group exhibited clear serial dependence, with systematic biases toward the orientation of stimuli shown in the preceding trials. Serial dependence in SCZ patients was largely comparable to that in the CNT group.

CONCLUSIONS

These findings challenge the prevailing notion of reduced serial dependence in SCZ, suggesting that observed differences between healthy CNT and patients may depend on aspects of perceptual or cognitive processing that are currently not understood.

Predictive Processing in Autism Spectrum Disorder: The Atypical Iterative Prior Updating Account

Background

The nature of predictive-processing differences between individuals with autism spectrum disorder (ASD) and typically developing (TD) individuals remains contested. Some studies have reported impaired predictive processing in ASD, while others have suggested intact but atypical learning dynamics.

Methods

We investigated duration reproduction tasks under high- and low-volatility settings to examine the updating dynamics of prior beliefs and sensory estimate updating in individuals with ASD (n = 32) and TD counterparts (n = 32). Using a two-state Bayesian model, we analyzed how the participants updated their prior beliefs and perceptual estimates and how these updates affected their behavior over time.

Results

Individuals with ASD integrated prior knowledge similarly to TD control participants for perceptual estimates. However, they relied more heavily on sensory input for iteratively updating their prior beliefs, perceiving events as less interconnected. This heightened reliance on sensory inputs led to the initial underweighting of priors in perceptual estimates, resulting in a weaker central tendency early in sessions. Over time, ASD participants adapted, reaching integration weights comparable to those of TD control participants by the end of the session. These findings suggest that predictive processing in ASD is characterized by distinct updating dynamics, not an inability to form or use prior effectively.

Conclusions

Our study highlights a unique interplay between sensory inputs and prior beliefs in ASD, where greater reliance on sensory inputs during prior updating influences adaptation speed and intertrial dynamics. This process clarifies inconsistencies in the literature and underscores the role of interactive updating in predictive processing differences between individuals with ASD and TD individuals.

Intact Susceptibility to Visual Illusions in Autistic Individuals

Altered sensory perception, a core characteristic of autism, has been attributed to attenuated use of stimuli context or prior information in perception. Reduced susceptibility to perceptual illusions was extensively used to support these accounts for autistic perception. However, empirical evidence has been inconsistent. The current study systematically investigated susceptibility to size illusions in autistic and non-autistic individuals using a standardized psychophysical battery. Eighty-one participants, 41 autistic and 40 non-autistic individuals, completed the Ben-Gurion University Test for Perceptual Illusions (BTPI), measuring susceptibility to the Ponzo, Ebbinghaus, and Height-width illusions. The results demonstrate clear evidence for susceptibility to illusions in the perception of size both in the autistic and non-autistic groups. No significant differences were found between groups in the magnitude of illusion on the perceived size, or on the perceptual resolutions of size (discrimination thresholds) in any of the illusory settings tested. The results challenge current theories suggesting reduced reliance on priors or enhanced sensory measurement in autism. Instead, using robust psychophysical methods, the study provides clear evidence for autistic people forming priors and using long-term knowledge in perception.

Autistic traits relate to reduced reward sensitivity in learning from point-light displays (PLDs)

A number of studies have linked autistic traits to difficulties in learning from social (versus non-social) stimuli. However, these stimuli are often difficult to match on low-level visual properties, which is especially important given the impact of autistic traits on sensory processing. Additionally, studies often fail to account for dissociable aspects of the learning process in the specification of model parameters (learning rates and reward sensitivity). Here, we investigate whether learning deficits in individuals with high autistic traits exhibit deficits when learning from facial point-light displays (PLDs) depicting emotional expressions. Social and non-social stimuli were created from random arrangements of the same number of point-lights and carefully matched on low-level visual properties. Neurotypical participants (N = 63) were assessed using the autism spectrum quotient (AQ) and completed a total of 96 trials in a reinforcement learning task. Although linear multi-level modelling did not indicate learning deficits, pre-registered computational modelling using a Rescorla-Wagner framework revealed that higher autistic traits were associated with reduced reward sensitivity in the win domain, demonstrating an attenuated response to received feedback during learning. These findings suggest that autistic traits can significantly impact learning from PLD feedback beyond a general deficit in learning rates.

Cognitive flexibility in autism: How task predictability and sex influence performances

While cognitive flexibility challenges are frequently reported in autistic individuals, inconsistencies in the findings prompt further investigation into the factors influencing this flexibility. We suggest that unique aspects of the predictive brain in autistic individuals might contribute to these challenges, potentially varying by sex. Our study aimed to test these hypotheses by examining cognitive flexibility under different predictability conditions in a sample including a similar number of males and females. We conducted an online study with 263 adults (127 with an autism diagnosis), where participants completed a flexibility task under varying levels of predictability (unpredictable, moderately predictable, and predictable). Our results indicate that as task predictability increases, performance improves; however, the response time gap between autistic and non-autistic individuals also widens. Moreover, we observe significant differences between autistic males and females, which differ from non-autistic individuals, highlighting the need to consider sex differences in research related to the cognition of autistic individuals. Overall, our findings contribute to a better understanding of cognitive flexibility and sex differences in autism in light of predictive brain theories and suggest avenues for further research.

Serial dependence in orientation is weak at the perceptual stage but intact at the response stage in autistic adults

Recent studies have suggested that autistic perception can be attributed to atypical Bayesian inference; however, it remains unclear whether the atypical Bayesian inference originates in the perceptual or post-perceptual stage or both. This study examined serial dependence in orientation at the perceptual and response stages in autistic and neurotypical adult groups. Participants comprised 17 autistic and 23 neurotypical adults. They reproduced the orientation of a Gabor stimulus in every odd trial or its mirror in every even trial. In the similar-stimulus session, a right-tilted Gabor stimulus was always presented; hence, serial dependence at the perceptual stage was presumed to occur because the perceived orientation was similar throughout the session. In the similar-response session, right- and left-tilted Gabor patches were alternately presented; thus serial dependence was presumed to occur because the response orientations were similar. Significant serial dependence was observed only in neurotypical adults for the similar-stimulus session, whereas it was observed in both groups for the similar-response session. Moreover, no significant correlation was observed between serial dependence and sensory profile. These findings suggest that autistic individuals possess atypical Bayesian inference at the perceptual stage and that sensory experiences in their daily lives are not attributable only to atypical Bayesian inference.

Representation of a perceptual bias in the prefrontal cortex

Perception is influenced by sensory stimulation, prior knowledge, and contextual cues, which collectively contribute to the emergence of perceptual biases. However, the precise neural mechanisms underlying these biases remain poorly understood. This study aims to address this gap by analyzing neural recordings from the prefrontal cortex (PFC) of monkeys performing a vibrotactile frequency discrimination task. Our findings provide empirical evidence supporting the hypothesis that perceptual biases can be reflected in the neural activity of the PFC. We found that the state-space trajectories of PFC neuronal activity encoded a warped representation of the first frequency presented during the task. Remarkably, this distorted representation of the frequency aligned with the predictions of its Bayesian estimator. The identification of these neural correlates expands our understanding of the neural basis of perceptual biases and highlights the involvement of the PFC in shaping perceptual experiences. Similar analyses could be employed in other delayed comparison tasks and in various brain regions to explore where and how neural activity reflects perceptual biases during different stages of the trial.

Autism spectrum disorder variation as a computational trade-off via dynamic range of neuronal population responses

Individuals diagnosed with autism spectrum disorder (ASD) show neural and behavioral characteristics differing from the neurotypical population. This may stem from a computational principle that relates inference and computational dynamics to the dynamic range of neuronal population responses, reflecting the signal levels for which the system is responsive. In the present study, we showed that an increased dynamic range (IDR), indicating a gradual response of a neuronal population to changes in input, accounts for neural and behavioral variations in individuals diagnosed with ASD across diverse tasks. We validated the model with data from finger-tapping synchronization, orientation reproduction and global motion coherence tasks. We suggested that increased heterogeneity in the half-activation point of individual neurons may be the biological mechanism underlying the IDR in ASD. Taken together, this model provides a proof of concept for a new computational principle that may account for ASD and generates new testable and distinct predictions regarding its behavioral, neural and biological foundations.

Reduced benefit from long-term item frequency contributes to short-term memory deficits in dyslexia

Dyslexia, a specific difficulty in acquiring proficient reading, is also characterized by reduced short-term memory (STM) capacity. Extensive research indicates that individuals with developmental dyslexia (IDDs) benefit less from exposure, and this hampers their long-term knowledge accumulation. It is well established that long-term knowledge has a great effect on performance in STM tasks, and thus IDDs' reduced benefit of exposure could potentially reduce their relative performance in such tasks, especially when frequent items, such as digit-words, are used. In this study we used a standard, widely used, STM assessment: the Digit Span subtest from the Wechsler Adult Intelligence Scale. The task was conducted twice: in native language and in second language. As exposure to native language is greater than exposure to second language, we predicted that IDDs' performance in the task administered in native language will reveal a larger group difference as compared to second language, due to IDDs' reduced benefit of item frequency. The prediction was confirmed, in line with the hypothesis that reduced STM in dyslexia to a large extent reflects reduced benefits from long-term item frequency and not a reduced STM per se.

Fast updating of stimulus history reveals weak internal representations of faces in autism

Atypical perception has been widely reported in autism spectrum disorders, and deficits in face recognition, specifically, are argued to be closely associated with social impairment experienced by these individuals. However, it is still debated (a) whether deficits are perceptually based, and (b) what the role is of experience-based refinements of perceptual face representations in autism. We investigated the effect of short- and long-term experienced stimulus history on face processing. Autistic and non-autistic individuals performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. Use of stimulus statistics was measured by testing the gravitation of face representations towards, the mean of a range of morphed faces around which they were sampled (regression-to-the-mean). The results show that unlike non-autistic individuals, representations of own- and other-race faces were equally biased by stimulus statistics in autistic individuals. Moreover, autistic individuals used the most recently exposed faces without forming a strong internal representation based on the overall experienced faces, indicating a weaker internal model of the "typical" averaged face. This accumulated history of faces may underlie typical face specialization, and thus may account for the reduced specialization for own-race faces shown in autism. The results shed light on the way autistic people process and recognize faces, and on the basic mechanisms underlying atypical face perception.

Perceptual anchoring: Children with dyslexia benefit less than controls from contextual repetitions in speech processing

OBJECTIVES

Individuals with dyslexia perceive and utilize statistical features in the auditory input deficiently. The present study investigates whether affected children also benefit less from repeating context tones as perceptual anchors for subsequent speech processing.

METHODS

In an event-related potential study, eleven-year-old children with dyslexia (n = 21) and without dyslexia (n = 20) heard syllable pairs, with the first syllable either receiving a constant pitch (anchor) or variable pitch (no-anchor), while second syllables were identical across conditions.

RESULTS

Children with and without dyslexia showed smaller auditory P2 responses to constant-pitch versus variable-pitch first syllables, while only control children additionally showed smaller N1 and faster P1 responses. This suggests less automatic processing of anchor repetitions in dyslexia. For the second syllables, both groups showed faster P2 responses following anchor than no-anchor first syllables, but only controls additionally showed smaller P2 responses.

CONCLUSIONS

Children with and without dyslexia show differences in anchor effects. While both groups seem to allocate less attention to speech stimuli after contextual repetitions, children with dyslexia display less facilitation in speech processing from acoustic anchors.

SIGNIFICANCE

Altered anchoring in the linguistic domain may contribute to the difficulties of individuals with dyslexia in establishing long-term representations of speech.

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.

The distinct development of stimulus and response serial dependence

Serial dependence (SD) is a phenomenon wherein current perceptions are biased by the previous stimulus and response. This helps to attenuate perceptual noise and variability in sensory input and facilitates stable ongoing perceptions of the environment. However, little is known about the developmental trajectory of SD. This study investigates how the stimulus and response biases of the SD effect develop across three age groups. Conventional analyses, in which previous stimulus and response biases were assessed separately, revealed significant changes in the biases over time. Previous stimulus bias shifted from repulsion to attraction, while previous response bias evolved from attraction to greater attraction. However, there was a strong correlation between stimulus and response orientations. Therefore, a generalized linear mixed-effects (GLME) analysis that simultaneously considered both previous stimulus and response, outperformed separate analyses. This revealed that previous stimulus and response resulted in two distinct biases with different developmental trajectories. The repulsion bias of previous stimulus remained relatively stable across all age groups, whereas the attraction bias of previous response was significantly stronger in adults than in children and adolescents. These findings demonstrate that the repulsion bias towards preceding stimuli is established early in the developing brain (at least by around 10 years old), while the attraction bias towards responses is not fully developed until adulthood. Our findings provide new insights into the development of the SD phenomenon and how humans integrate two opposing mechanisms into their perceptual responses to external input during development.

Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data

Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a revolutionary approach to investigate how the brain encodes information. By considering complex interactions among spatio-temporal features at the individual level, MVPA overcomes the limitations of univariate techniques, which often fail to account for the significant inter- and intra-individual neural variability. This is particularly relevant when studying clinical populations, and therefore MVPA of EEG data has recently started to be employed as a tool to study cognition in brain disorders. Here, we review the insights offered by this methodology in the study of anomalous patterns of neural activity in conditions such as autism, ADHD, schizophrenia, dyslexia, neurological and neurodegenerative disorders, within different cognitive domains (perception, attention, memory, consciousness). Despite potential drawbacks that should be attentively addressed, these studies reveal a peculiar sensitivity of MVPA in unveiling dysfunctional and compensatory neurocognitive dynamics of information processing, which often remain blind to traditional univariate approaches. Such higher sensitivity in characterizing individual neurocognitive profiles can provide unique opportunities to optimise assessment and promote personalised interventions.

Perceptual narrowing continues throughout childhood: Evidence from specialization of face processing

Face recognition shows a long trajectory of development and is known to be closely associated with the development of social skills. However, it is still debated whether this long trajectory is perceptually based and what the role is of experience-based refinements of face representations throughout development. We examined the effects of short and long-term experienced stimulus history on face processing, using regression biases of face representations towards the experienced mean. Children and adults performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. The results show that face recognition continues to improve after 9 years of age, with more pronounced improvements for own-race faces. This increased narrowing with age is also indicated by similar use of stimulus statistics for own-race and other-race faces in children, contrary to the different use of the overall stimulus history for these two face types in adults. Increased face proficiency in adulthood renders the perceptual system less tuned to other-race face statistics. Altogether, the results demonstrate associations between levels of specialization and the extent to which perceptual representations become narrowly tuned with age.

Emergent perceptual biases from state-space geometry in trained spiking recurrent neural networks

A stimulus held in working memory is perceived as contracted toward the average stimulus. This contraction bias has been extensively studied in psychophysics, but little is known about its origin from neural activity. By training recurrent networks of spiking neurons to discriminate temporal intervals, we explored the causes of this bias and how behavior relates to population firing activity. We found that the trained networks exhibited animal-like behavior. Various geometric features of neural trajectories in state space encoded warped representations of the durations of the first interval modulated by sensory history. Formulating a normative model, we showed that these representations conveyed a Bayesian estimate of the interval durations, thus relating activity and behavior. Importantly, our findings demonstrate that Bayesian computations already occur during the sensory phase of the first stimulus and persist throughout its maintenance in working memory, until the time of stimulus comparison.

Perception and adaptation of receptive prosody in autistic adolescents

A fundamental aspect of language processing is inferring others' minds from subtle variations in speech. The same word or sentence can often convey different meanings depending on its tempo, timing, and intonation-features often referred to as prosody. Although autistic children and adults are known to experience difficulty in making such inferences, the science remains unclear as to why. We hypothesize that detail-oriented perception in autism may interfere with the inference process if it lacks the adaptivity required to cope with the variability ubiquitous in human speech. Using a novel prosodic continuum that shifts the sentence meaning gradiently from a statement (e.g., "It's raining") to a question (e.g., "It's raining?"), we have investigated the perception and adaptation of receptive prosody in autistic adolescents and two groups of non-autistic controls. Autistic adolescents showed attenuated adaptivity in categorizing prosody, whereas they were equivalent to controls in terms of discrimination accuracy. Combined with recent findings in segmental (e.g., phoneme) recognition, the current results provide the basis for an emerging research framework for attenuated flexibility and reduced influence of contextual feedback as a possible source of deficits that hinder linguistic and social communication in autism.

Erroneous predictive coding across brain hierarchies in a non-human primate model of autism spectrum disorder

In autism spectrum disorder (ASD), atypical sensory experiences are often associated with irregularities in predictive coding, which proposes that the brain creates hierarchical sensory models via a bidirectional process of predictions and prediction errors. However, it remains unclear how these irregularities manifest across different functional hierarchies in the brain. To address this, we study a marmoset model of ASD induced by valproic acid (VPA) treatment. We record high-density electrocorticography (ECoG) during an auditory task with two layers of temporal control, and applied a quantitative model to quantify the integrity of predictive coding across two distinct hierarchies. Our results demonstrate a persistent pattern of sensory hypersensitivity and unstable predictions across two brain hierarchies in VPA-treated animals, and reveal the associated spatio-spectro-temporal neural signatures. Despite the regular occurrence of imprecise predictions in VPA-treated animals, we observe diverse configurations of underestimation or overestimation of sensory regularities within the hierarchies. Our results demonstrate the coexistence of the two primary Bayesian accounts of ASD: overly-precise sensory observations and weak prior beliefs, and offer a potential multi-layered biomarker for ASD, which could enhance our understanding of its diverse symptoms.

Super recognizers: Increased sensitivity or reduced biases? Insights from serial dependence

Super recognizers (SRs) are people that exhibit a naturally occurring superiority for processing facial identity. Despite the increase of SR research, the mechanisms underlying their exceptional abilities remain unclear. Here, we investigated whether the enhanced facial identity processing of SRs could be attributed to the lack of sequential effects, such as serial dependence. In serial dependence, perception of stimulus features is assimilated toward stimuli presented in previous trials. This constant error in visual perception has been proposed as a mechanism that promotes perceptual stability in everyday life. We hypothesized that an absence of this constant source of error in SRs could account for their superior processing-potentially in a domain-general fashion. We tested SRs (n = 17) identified via a recently proposed diagnostic framework (Ramon, 2021) and age-matched controls (n = 20) with two experiments probing serial dependence in the face and shape domains. In each experiment, observers were presented with randomly morphed face identities or shapes and were asked to adjust a face's identity or a shape to match the stimulus they saw. We found serial dependence in controls and SRs alike, with no difference in its magnitude across groups. Interestingly, we found that serial dependence impacted the performance of SRs more than that of controls. Taken together, our results show that enhanced face identity processing skills in SRs cannot be attributed to the lack of serial dependence. Rather, serial dependence, a beneficial nested error in our visual system, may in fact further stabilize the perception of SRs and thus enhance their visual processing proficiency.

Multiple talker processing in autistic adult listeners

Accommodating talker variability is a complex and multi-layered cognitive process. It involves shifting attention to the vocal characteristics of the talker as well as the linguistic content of their speech. Due to an interdependence between voice and phonological processing, multi-talker environments typically incur additional processing costs compared to single-talker environments. A failure or inability to efficiently distribute attention over multiple acoustic cues in the speech signal may have detrimental language learning consequences. Yet, no studies have examined effects of multi-talker processing in populations with atypical perceptual, social and language processing for communication, including autistic people. Employing a classic word-monitoring task, we investigated effects of talker variability in Australian English autistic (n = 24) and non-autistic (n = 28) adults. Listeners responded to target words (e.g., apple, duck, corn) in randomised sequences of words. Half of the sequences were spoken by a single talker and the other half by multiple talkers. Results revealed that autistic participants' sensitivity scores to accurately-spotted target words did not differ to those of non-autistic participants, regardless of whether they were spoken by a single or multiple talkers. As expected, the non-autistic group showed the well-established processing cost associated with talker variability (e.g., slower response times). Remarkably, autistic listeners' response times did not differ across single- or multi-talker conditions, indicating they did not show perceptual processing costs when accommodating talker variability. The present findings have implications for theories of autistic perception and speech and language processing.

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.

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.

Is she still angry? Intact learning but no updating of facial expressions priors in autism

Autistic people exhibit atypical use of prior information when processing simple perceptual stimuli; yet, it remains unclear whether and how these difficulties in using priors extend to complex social stimuli. Here, we compared autistic people without accompanying intellectual disability and nonautistic people in their ability to acquire an "emotional prior" of a facial expression and update this prior to a different facial expression of the same identity. Participants performed a two-interval same/different discrimination task between two facial expressions. To study the acquisition of the prior, we examined how discrimination was modified by the contraction of the perceived facial expressions toward the average of presented stimuli (i.e., regression to the mean). At first, facial expressions surrounded one average emotional prior (mostly sad or angry), and then the average switched (to mostly angry or sad, accordingly). Autistic people exhibited challenges in facial discrimination, and yet acquired the first prior, demonstrating typical regression-to-the-mean effects. However, unlike nonautistic people, autistic people did not update their perception to the second prior, suggesting they are less flexible in updating an acquired prior of emotional expressions. Our findings shed light on the perception of emotional expressions, one of the most pressing challenges in autism.

Unifying network model links recency and central tendency biases in working memory

The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain's ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience - producing short-term sensory history biases - naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution's mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.

Reduced categorical learning of faces in dyslexia

The perception of phonological categories in dyslexia is less refined than in typically developing (TD) individuals. Traditionally, this characteristic was considered unique to phonology, yet many studies showed non-phonological perceptual difficulties. Importantly, measuring the dynamics of cortical adaptation, associated with category acquisition, revealed a broadly distributed faster decay of cortical adaptation. Taken together, these observations suggest that the acquisition of perceptual categories in dyslexia may be slower across modalities. To test this, we tested adult individuals with developmental dyslexia (IDDs) and TDs on learning of two unknown faces, yielding face-specific categorization. Initial accuracy was similar in the two groups, yet practice-induced increase in accuracy was significantly larger in TDs. Modeling the learning process (using Drift Diffusion Model) revealed that TDs' steeper learning results from a larger increase in their effective face-specific signal. We propose that IDDs' slower item-specific categorical learning of unknown faces indicates that slower categorical learning in dyslexia is a core, domain-general difficulty.

A unifying theory explains seemingly contradictory biases in perceptual estimation

Perceptual biases are widely regarded as offering a window into the neural computations underlying perception. To understand these biases, previous work has proposed a number of conceptually different, and even seemingly contradictory, explanations, including attraction to a Bayesian prior, repulsion from the prior due to efficient coding and central tendency effects on a bounded range. We present a unifying Bayesian theory of biases in perceptual estimation derived from first principles. We demonstrate theoretically an additive decomposition of perceptual biases into attraction to a prior, repulsion away from regions with high encoding precision and regression away from the boundary. The results reveal a simple and universal rule for predicting the direction of perceptual biases. Our theory accounts for, and yields, new insights regarding biases in the perception of a variety of stimulus attributes, including orientation, color and magnitude. These results provide important constraints on the neural implementations of Bayesian computations.

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.

Frequency-specific contributions to auditory perceptual priors: Testing the predictive-coding hypothesis

Perceptual priors formed by recent stimuli bias our immediate percept. These priors, expressing our implicit expectations, affect both high- and low-level processing stages. Yet, the nature of the inter-level interaction is unknown. Do priors operate top-down and bias low-level features toward recently experienced objects (predictive-coding hypothesis), or are low-level biases bottom-up driven and formed by local memory circuits? To decipher between these options in auditory perception, we used the "missing fundamental illusion", enabling the dissociation of low-level components from the high-level pitch. Surprisingly, in contrast to predictive coding, when the fundamental frequency was missing, pitch contraction across timbre categories was not found to the previously perceived high-level pitch, but to the physically present frequency. This bottom-up contribution of low-level memory components to perceptual priors, operating independently of recent high-level percepts, may stabilize the perceptual organization and underlie continuity between similar low-level features belonging to different object categories in the auditory modality.

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.

Atypical reliance on monocular visual pathway for face and word recognition in developmental dyslexia

Studies with individuals with developmental dyslexia (DD) have documented impaired perception of words and faces, both of which are domains of visual expertise for human adults. In this study, we examined a possible mechanism that might be associated with the impaired acquisition of visual expertise for words and faces in DD, namely, the atypical engagement of the monocular visual pathway. Participants with DD and typical readers (TR) judged whether a pair of sequentially presented unfamiliar faces or nonwords were the same or different, and the pair of stimuli were displayed in an eye-specific fashion using a stereoscope. Based on evidence of greater reliance on subcortical structures early in development, we predicted differences between the groups in the engagement of lower (monocular) versus higher (binocular) regions of the visual pathways. Whereas the TR group showed a monocular advantage for both stimulus types, the DD participants evinced a monocular advantage for faces and words that was much greater than that measured in the TRs. These findings indicate that the DD individuals have enhanced subcortical engagement and that this might arise from the failure to fine-tune cortical correlates mediating the discrimination of homogeneous exemplars in domains of expertise.

Refinement of face representations by exposure reveals different time scales of biases in face processing

Experience modulates face processing abilities so that face discrimination and recognition improve with development, especially for more frequently experienced faces (e.g., own-race faces). Although advanced models describe how experience generally modulates perception, the mechanism by which exposure refines internal perceptual representations of faces is unknown. To address this issue, we investigated the effect of short- and long-term experienced stimulus history on face processing. Participants performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. Use of stimulus statistics was measured by testing the gravitation of face representations towards the mean of a range of morphed faces around which they were sampled (regression-to-the-mean). The results demonstrated regression of face representations towards the experienced mean and the retention of stimulus statistics over days. In trials where regression facilitated discrimination, the bias diminished the otherwise disadvantage of other-race over own-races faces. The dynamics of the perceptual bias, probed by trial-by-trial performance, further indicated different timescales of the bias, depending on perceptual expertise: people with weak face-recognition skills showed the use of a stable reference, built on long-term statistics accumulated over many trials, along with an updating of this reference by recent trials. In contrast, the strong face recognizers showed a different pattern where sequential effects mostly contributed to discrimination, with relatively minimal reliance on the long-term average for other-race faces. The findings suggest a mechanism by which exposure refines face representations and reveal, for the first time in adults, associations between levels of specialization of perceptual representations and the extent to which these representations become narrowly tuned.

Neurophysiological measures and correlates of cognitive load in attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and dyslexia: A scoping review and research recommendations

Working memory is integral to a range of critical cognitive functions such as reasoning and decision-making. Although alterations in working memory have been observed in neurodivergent populations, there has been no review mapping how cognitive load is measured in common neurodevelopmental conditions such as attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD) and dyslexia. This scoping review explores the neurophysiological measures used to study cognitive load in these specific populations. Our findings highlight that electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are the most frequently used methods, with a limited number of studies employing functional near-infrared spectroscopy (fNIRs), magnetoencephalography (MEG) or eye-tracking. Notably, eye-related measures are less commonly used, despite their prominence in cognitive load research among neurotypical individuals. The review also highlights potential correlates of cognitive load, such as neural oscillations in the theta and alpha ranges for EEG studies, blood oxygenation level-dependent (BOLD) responses in lateral and medial frontal brain regions for fMRI and fNIRS studies and eye-related measures such as pupil dilation and blink rate. Finally, critical issues for future studies are discussed, including the technical challenges associated with multimodal approaches, the possible impact of atypical features on cognitive load measures and balancing data richness with participant well-being. These insights contribute to a more nuanced understanding of cognitive load measurement in neurodivergent populations and point to important methodological considerations for future neuroscientific research in this area.

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.

Prolonged neural encoding of visual information in autism

Autism spectrum disorder (ASD) is associated with a hyper-focused visual attentional style, impacting higher-order social and affective domains. The understanding of such peculiarity can benefit from the use of multivariate pattern analysis (MVPA) of high-resolution electroencephalography (EEG) data, which has proved to be a powerful technique to investigate the hidden neural dynamics orchestrating sensory and cognitive processes. Here, we recorded EEG in typically developing (TD) children and in children with ASD during a visuo-spatial attentional task where attention was exogenously captured by a small (zoom-in) or large (zoom-out) cue in the visual field before the appearance of a target at different eccentricities. MVPA was performed both in the cue-locked period, to reveal potential differences in the modulation of the attentional focus, and in the target-locked period, to reveal potential cascade effects on stimulus processing. Cue-locked MVPA revealed that while in the TD group the pattern of neural activity contained information about the cue mainly before the target appearance, the ASD group showed a temporally sustained and topographically diffuse significant decoding of the cue neural response even after the target onset, suggesting a delayed extinction of cue-related neural activity. Crucially, this delayed extinction positively correlated with behavioral measures of attentional hyperfocusing. Results of target-locked MVPA were coherent with a hyper-focused attentional profile, highlighting an earlier and stronger decoding of target neural responses in small cue trials in the ASD group. The present findings document a spatially and temporally overrepresented encoding of visual information in ASD, which can constitute one of the main reasons behind their peculiar cognitive style.

Do we all synch alike? Brain-body-environment interactions in ASD

Autism Spectrum Disorder (ASD) is characterized by rigidity of routines and restricted interests, and atypical social communication and interaction. Recent evidence for altered synchronization of neuro-oscillatory brain activity with regularities in the environment and of altered peripheral nervous system function in ASD present promising novel directions for studying pathophysiology and its relationship to ASD clinical phenotype. Human cognition and action are significantly influenced by physiological rhythmic processes that are generated by both the central nervous system (CNS) and the autonomic nervous system (ANS). Normally, perception occurs in a dynamic context, where brain oscillations and autonomic signals synchronize with external events to optimally receive temporally predictable rhythmic information, leading to improved performance. The recent findings on the time-sensitive coupling between the brain and the periphery in effective perception and successful social interactions in typically developed highlight studying the interactions within the brain-body-environment triad as a critical direction in the study of ASD. Here we offer a novel perspective of autism as a case where the temporal dynamics of brain-body-environment coupling is impaired. We present evidence from the literature to support the idea that in autism the nervous system fails to operate in an adaptive manner to synchronize with temporally predictable events in the environment to optimize perception and behavior. This framework could potentially lead to novel biomarkers of hallmark deficits in ASD such as cognitive rigidity and altered social interaction.

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.

From neural noise to co-adaptability: Rethinking the multifaceted architecture of motor variability

In the last decade, the source and the functional meaning of motor variability have attracted considerable attention in behavioral and brain sciences. This construct classically combined different levels of description, variable internal robustness or coherence, and multifaceted operational meanings. We provide here a comprehensive review of the literature with the primary aim of building a precise lexicon that goes beyond the generic and monolithic use of motor variability. In the pars destruens of the work, we model three domains of motor variability related to peculiar computational elements that influence fluctuations in motor outputs. Each domain is in turn characterized by multiple sub-domains. We begin with the domains of noise and differentiation. However, the main contribution of our model concerns the domain of adaptability, which refers to variation within the same exact motor representation. In particular, we use the terms learning and (social)fitting to specify the portions of motor variability that depend on our propensity to learn and on our largely constitutive propensity to be influenced by external factors. A particular focus is on motor variability in the context of the sub-domain named co-adaptability. Further groundbreaking challenges arise in the modeling of motor variability. Therefore, in a separate pars construens, we attempt to characterize these challenges, addressing both theoretical and experimental aspects as well as potential clinical implications for neurorehabilitation. All in all, our work suggests that motor variability is neither simply detrimental nor beneficial, and that studying its fluctuations can provide meaningful insights for future research.

Effect of presentation rate on auditory processing in Rett syndrome: event-related potential study

BACKGROUND

Rett syndrome (RS) is a rare neurodevelopmental disorder characterized by mutations in the MECP2 gene. Patients with RS have severe motor abnormalities and are often unable to walk, use hands and speak. The preservation of perceptual and cognitive functions is hard to assess, while clinicians and care-givers point out that these patients need more time to process information than typically developing peers. Neurophysiological correlates of auditory processing have been also found to be distorted in RS, but sound presentation rates were relatively quick in these studies (stimulus onset asynchrony, SOA < 1000 ms). As auditory event-related potential (ERP) is typically increased with prolongation of SOA we aim to study if SOA prolongation might compensate for observed abnormalities.

METHODS

We presented a repetitive stimulus (1000 Hz) at three different SOAs of 900 ms, 1800 ms, and 3600 ms in children with RS (N = 24, Mean age = 9.0 ± 3.1) and their typical development (TD) peers (N = 27, Mean age = 9.7 ± 3.4) while recording 28-channels electroencephalogram, EEG. Some RS participants (n = 10) did not show clear ERP and were excluded from the analysis.

RESULTS

Major ERP components (here assessed as N1P1 and P2N1 peak-to-peak values) were smaller at SOA 900 than at longer SOAs in both groups, pointing out that the basic mechanism of adaptation in the auditory system is preserved in at least in RS patients with evident ERPs. At the same time the latencies of these components were significantly delayed in the RS than in TD. Moreover, late components (P2N1 and N2P2) were drastically reduced in Rett syndrome irrespective of the SOA, suggesting a largely affected mechanism of integration of upcoming sensory input with memory. Moreover, developmental stagnation of auditory ERP characterized patients with RS: absence of typical P2N1 enlargement and P1 and N1 shortening with age at least for shortest SOA.

LIMITATIONS

We could not figure out the cause for the high percentage of no-evident ERP RS participants and our final sample of the RS group was rather small. Also, our study did not include a control clinical group.

CONCLUSIONS

Thus, auditory ERPs inform us about abnormalities within auditory processing that cannot be fully overcomed by slowing presentation rate.

Testing predictive coding theories of autism spectrum disorder using models of active inference

Several competing neuro-computational theories of autism have emerged from predictive coding models of the brain. To disentangle their subtly different predictions about the nature of atypicalities in autistic perception, we performed computational modelling of two sensorimotor tasks: the predictive use of manual gripping forces during object lifting and anticipatory eye movements during a naturalistic interception task. In contrast to some accounts, we found no evidence of chronic atypicalities in the use of priors or weighting of sensory information during object lifting. Differences in prior beliefs, rates of belief updating, and the precision weighting of prediction errors were, however, observed for anticipatory eye movements. Most notably, we observed autism-related difficulties in flexibly adapting learning rates in response to environmental change (i.e., volatility). These findings suggest that atypical encoding of precision and context-sensitive adjustments provide a better explanation of autistic perception than generic attenuation of priors or persistently high precision prediction errors. Our results did not, however, support previous suggestions that autistic people perceive their environment to be persistently volatile.

Using representational similarity analysis to reveal category and process specificity in visual object recognition

Cross-condition comparisons on neurodevelopmental conditions are central in neurodiversity research. In the realm of visual perception, the performance of participants with different category-specific disorders such as developmental prosopagnosia (problems with faces) and dyslexia (problems with words) have contributed to understanding of perceptual processes involved in word and face recognition. Alterations in face and word recognition are present in several neurodiverse populations, and improved knowledge about their relationship may increase our understanding of this variability of impairment. The present study investigates organizing principles of visual object processing and their implications for developmental disorders of recognition. Some accounts suggest that distinct mechanisms are responsible for recognizing objects of different categories, while others propose that categories share or even compete for cortical resources. We took an individual differences approach to estimate the relationship between abilities in recognition. Neurotypical participants (N = 97 after outlier exclusion) performed a match-to-sample task with faces, houses, and pseudowords. Either individual features or feature configurations were manipulated. To estimate the separability of visual recognition mechanisms, we used representational similarity analysis (RSA) where correlational matrices for accuracy were compared to predicted data patterns. Recognition abilities separated into face recognition on one hand and house/pseudoword recognition on the other, indicating that face recognition may rely on relatively selective mechanisms in neurotypicals. We also found evidence for a general visual object recognition mechanism, while some combinations of category (faces, houses, words) and processing type (featural, configural) likely rely on additional mechanisms. Developmental conditions may therefore reflect combinations of impaired and intact aspects of specific and general visual object recognition mechanisms, where featural and configural processes for one object category separate from the featural or configural processing of another. More generally, RSA is a promising approach for advancing understanding of neurodiversity, including shared aspects and distinctions between neurodevelopmental conditions of visual recognition.

Long- and short-term history effects in a spiking network model of statistical learning

The statistical structure of the environment is often important when making decisions. There are multiple theories of how the brain represents statistical structure. One such theory states that neural activity spontaneously samples from probability distributions. In other words, the network spends more time in states which encode high-probability stimuli. Starting from the neural assembly, increasingly thought of to be the building block for computation in the brain, we focus on how arbitrary prior knowledge about the external world can both be learned and spontaneously recollected. We present a model based upon learning the inverse of the cumulative distribution function. Learning is entirely unsupervised using biophysical neurons and biologically plausible learning rules. We show how this prior knowledge can then be accessed to compute expectations and signal surprise in downstream networks. Sensory history effects emerge from the model as a consequence of ongoing learning.

Stable perceptual phenotype of the magnitude of history biases even in the face of global task complexity

According to a Bayesian framework, visual perception requires active interpretation of noisy sensory signals in light of prior information. One such mechanism, serial dependence, is thought to promote perceptual stability by assimilating current percepts with recent stimulus history. Combining a delayed orientation-adjustment paradigm with predictable (study 1) or unpredictable (study 2) task structure, we test two key predictions of this account in a novel context: first, that serial dependence should persist even in variable environments, and, second, that, within a given observer and context, this behavioral bias should be stable from one occasion to the next. Relying on data of 41 human volunteers and two separate experimental sessions, we confirm both hypotheses. Group-level, attractive serial dependence remained strong even in the face of volatile settings with multiple, unpredictable types of tasks, and, despite considerable interindividual variability, within-subject patterns of attractive and repulsive stimulus-history biases were highly stable from one experimental session to the next. In line with the hypothesized functional role of serial dependence, we propose that, together with previous work, our findings suggest the existence of a more general individual-specific fingerprint with which the past shapes current perception. Congruent with the Bayesian account, interindividual differences may then result from differential weighting of sensory evidence and prior information.

Intact predictive processing in autistic adults: evidence from statistical learning

Impairment in predictive processes gained a lot of attention in recent years as an explanation for autistic symptoms. However, empirical evidence does not always underpin this framework. Thus, it is unclear what aspects of predictive processing are affected in autism spectrum disorder. In this study, we tested autistic adults on a task in which participants acquire probability-based regularities (that is, a statistical learning task). Twenty neurotypical and 22 autistic adults learned a probabilistic, temporally distributed regularity for about 40 min. Using frequentist and Bayesian methods, we found that autistic adults performed comparably to neurotypical adults, and the dynamics of learning did not differ between groups either. Thus, our study provides evidence for intact statistical learning in autistic adults. Furthermore, we discuss potential ways this result can extend the scope of the predictive processing framework, noting that atypical processing might not always mean a deficit in performance.

A theory of autism bridging across levels of description

Autism impacts a wide range of behaviors and neural functions. As such, theories of autism spectrum disorder (ASD) are numerous and span different levels of description, from neurocognitive to molecular. We propose how existent behavioral, computational, algorithmic, and neural accounts of ASD may relate to one another. Specifically, we argue that ASD may be cast as a disorder of causal inference (computational level). This computation relies on marginalization, which is thought to be subserved by divisive normalization (algorithmic level). In turn, divisive normalization may be impaired by excitatory-to-inhibitory imbalances (neural implementation level). We also discuss ASD within similar frameworks, those of predictive coding and circular inference. Together, we hope to motivate work unifying the different accounts of ASD.

Neural correlates of statistical learning in developmental dyslexia: An electroencephalography study

The human brain extracts statistical regularities from the surrounding environment in a process called statistical learning. Behavioural evidence suggests that developmental dyslexia affects statistical learning. However, surprisingly few studies have assessed how developmental dyslexia affects the neural processing underlying this type of learning. We used electroencephalography to explore the neural correlates of an important aspect of statistical learning - sensitivity to transitional probabilities - in individuals with developmental dyslexia. Adults diagnosed with developmental dyslexia (n = 17) and controls (n = 19) were exposed to a continuous stream of sound triplets. Every so often, a triplet ending had a low transitional probability given the triplet's first two sounds ("statistical deviants"). Furthermore, every so often a triplet ending was presented from a deviant location ("acoustic deviants"). We examined mismatch negativity elicited by statistical deviants (sMMN), and MMN elicited by location deviants (i.e., acoustic changes). Acoustic deviants elicited a MMN which was larger in the control group than in the developmental dyslexia group. Statistical deviants elicited a small, yet significant, sMMN in the control group, but not in the developmental dyslexia group. However, the difference between the groups was not significant. Our findings indicate that the neural mechanisms underlying pre-attentive acoustic change detection and implicit statistical auditory learning are both affected in developmental dyslexia.

The Role of Visual Factors in Dyslexia

What are the causes of dyslexia? Decades of research reflect a determined search for a single cause where a common assumption is that dyslexia is a consequence of problems with converting phonological information into lexical codes. But reading is a highly complex activity requiring many well-functioning mechanisms, and several different visual problems have been documented in dyslexic readers. We critically review evidence from various sources for the role of visual factors in dyslexia, from magnocellular dysfunction through accounts based on abnormal eye movements and attentional processing, to recent proposals that problems with high-level vision contribute to dyslexia. We believe that the role of visual problems in dyslexia has been underestimated in the literature, to the detriment of the understanding and treatment of the disorder. We propose that rather than focusing on a single core cause, the role of visual factors in dyslexia fits well with risk and resilience models that assume that several variables interact throughout prenatal and postnatal development to either promote or hinder efficient reading.

Neural correlates of hierarchical predictive processes in autistic adults

Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive mechanisms could underlie the autistic symptomatology, but little is known about their neural correlates. Twenty-six neurotypical (NT) and 26 autistic adults participated in an fMRI study where they performed an associative learning task in a volatile environment. By inverting a model of perceptual inference, we characterized the neural correlates of hierarchically structured predictions and prediction errors in ASD. Behaviorally, the predictive abilities of autistic adults were intact. Neurally, predictions were encoded hierarchically in both NT and ASD participants and biased their percepts. High-level predictions were following activity levels in a set of regions more closely in ASD than NT. Prediction errors yielded activation in shared regions in NT and ASD, but group differences were found in the anterior cingulate cortex and putamen. This study sheds light on the neural specificities of ASD that might underlie atypical predictive processing.

Context expectation influences the gait pattern biomechanics

Beyond classical aspects related to locomotion (biomechanics), it has been hypothesized that walking pattern is influenced by a combination of distinct computations including online sensory/perceptual sampling and the processing of expectations (neuromechanics). Here, we aimed to explore the potential impact of contrasting scenarios ("risky and potentially dangerous" scenario; "safe and comfortable" scenario) on walking pattern in a group of healthy young adults. Firstly, and consistently with previous literature, we confirmed that the scenario influences gait pattern when it is recalled concurrently to participants' walking activity (motor interference). More intriguingly, our main result showed that participants' gait pattern is also influenced by the contextual scenario when it is evoked only before the start of walking activity (motor expectation). This condition was designed to test the impact of expectations (risky scenario vs. safe scenario) on gait pattern, and the stimulation that preceded walking activity served as prior. Noteworthy, we combined statistical and machine learning (Support-Vector Machine classifier) approaches to stratify distinct levels of analyses that explored the multi-facets architecture of walking. In a nutshell, our combined statistical and machine learning analyses converge in suggesting that walking before steps is not just a paradox.

Cross-Modality Evidence for Reduced Choice History Biases in Psychosis-Prone Individuals

OBJECTIVES

Predictive processing posits that perception emerges from inferential processes within a hierarchical cortical system. Alterations of these processes may result in psychotic experiences, such as hallucinations and delusions. Central to the predictive processing account of psychosis is the notion of aberrant weights attributed to prior information and sensory input. Based on the notion that previous perceptual choices represent a relevant source of prior information, we here asked whether the propensity towards psychotic experiences may be related to altered choice history biases in perceptual decision-making.

METHODS

We investigated the relationship between choice history biases in perceptual decision-making and psychosis proneness in the general population. Choice history biases and their adaptation to experimentally induced changes in stimulus serial dependencies were investigated in decision-making tasks with auditory (experiment 1) and visual (experiment 2) stimuli. We further explored a potential compensatory mechanism for reduced choice history biases by reliance on predictive cross-modal cues.

RESULTS

In line with our preregistered hypothesis, psychosis proneness was associated with decreased choice history biases in both experiments. This association is generalized across conditions with and without stimulus serial dependencies. We did not find consistent evidence for a compensatory reliance on cue information in psychosis-prone individuals across experiments.

CONCLUSIONS

Our results show reduced choice history biases in psychosis proneness. A compensatory mechanism between implicit choice history effects and explicit cue information is not supported unequivocally by our data.