Predictive coding in autism spectrum disorder and attention deficit hyperactivity disorder

Pre-attentive and Attentive Auditory Event-related Potentials in Children With Attention-Deficit Hyperactivity Disorder and Autism

Abnormalities in auditory processing are believed to play a major role in autism and attention-deficit hyperactivity disorder (ADHD). Both conditions often co-occur in children, causing difficulties in deciding the most promising intervention. Event-related potentials (ERPs) have been investigated and are showing promise to act as potential biomarkers for both conditions. This study investigated mismatch negativity (MMN) using a passive listening task and P3b in an active auditory go/no-go discrimination task. Recordings were available from 103 children (24 females): 35 with ADHD, 27 autistic, 15 autistic children with co-occurring ADHD, and 26 neurotypical (NT) children. The age range considered was between 4 and 17 years, but varied between groups. The results revealed increases in the MMN and P3b amplitudes with age. Older children with ADHD exhibited smaller P3b amplitudes, while younger autistic children showed reduced MMN amplitudes in response to phoneme changes compared to their NT counterparts. Notably, children diagnosed with autism and ADHD did not follow this pattern; instead, they exhibited more similarities to NT children. The reduced amplitudes of phonetically elicited MMN in children with autism and reduced P3b in children with ADHD suggest that the two respective ERPs can act as potential biomarkers for each condition. However, optimisation and standardisation of the testing protocol, as well as longitudinal studies are required in order to translate these findings into clinical practice.

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.

Attentional ERPs in consumers of smoked and insufflated cocaine associated with neuropsychological performance

BACKGROUND

Cocaine consumption is associated with reduced attentional event-related potentials (ERPs), namely P3a and P3b, indicating bottom-up and top-down deficits respectively. At cognitive level, these impairments are larger for faster routes of administration (e.g., smoked cocaine [SC]) than slower routes (e.g., insufflated cocaine [IC]). Here we assess these ERPs considering the route of cocaine administration. We hypothesized that SC dependent (SCD) would exhibit reduced amplitude of the P3a, while both SCD and IC dependent (ICD) would show reduced amplitude of the P3b.

METHODS

We examined 25 SCD, 22 ICD matched by poly-consumption profiles, and 25 controls matched by demographic variables. We combined EEG data from the Global-Local task with behavioral data from attentional cognitive tasks.

RESULTS

At the behavioral level, SCD exhibited attentional deficits in both bottom-up and top-down processes, while ICD only showed a tendency for top-down deficits. The amplitude of P3a and P3b was lower in Users groups. We observed subtle route-based differences, with larger differences in the P3a for SCD and in the P3b for ICD. Neurophysiological and behavioral data converged, with the P3a associated to bottom-up performance and P3b to top-down.

CONCLUSIONS

Different routes of administration lead to distinct attentional neurocognitive profiles. Specifically, SCD showed greater attentional impairment, mainly at bottom-up/P3a, while ICD showed a trend of top-down/P3b deficits. These findings emphasize the crucial role of considering the route of administration in both clinical and research settings and support the use of attentional ERPs as valid measures for assessing attentional deficits in substance Dependence.

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.

Alpha oscillations encode Bayesian belief updating underlying attentional allocation in dynamic environments

In a dynamic environment, expectations of the future constantly change based on updated evidence and affect the dynamic allocation of attention. To further investigate the neural mechanisms underlying attentional expectancies, we employed a modified Central Cue Posner Paradigm in which the probability of cues being valid (that is, accurately indicated the upcoming target location) was manipulated. Attentional deployment to the cued location (α), which was governed by precision of predictions on previous trials, was estimated using a hierarchical Bayesian model and was included as a regressor in the analyses of electrophysiological (EEG) data. Our results revealed that before the target appeared, alpha oscillations (8∼13 Hz) for high-predictability cues (88 % valid) were significantly predicted by precision-dependent attention (α). This relationship was not observed under low-predictability conditions (69 % and 50 % valid cues). After the target appeared, precision-dependent attention (α) correlated with alpha band oscillations only in the valid cue condition and not in the invalid condition. Further analysis under conditions of significant attentional modulation by precision suggested a separate effect of cue orientation. These results provide new insights on how trial-by-trial Bayesian belief updating relates to alpha band encoding of environmentally-sensitive allocation of visual spatial attention.

Elevated EEG heartbeat-evoked potentials in adolescents with more ADHD symptoms

INTRODUCTION

Symptoms of attention deficit hyperactivity disorder (ADHD) are associated with a variety of mental abnormalities, but little is known about the perception and processing of internal signals, i.e., interoception, in individuals with ADHD symptoms. This study aimed to investigate the association between ADHD symptoms and the heartbeat-evoked potential (HEP), known as a neural correlate of automatic interoceptive processing of cardiac signals, in adolescents.

METHODS

HEPs of 47 healthy adolescent participants (53.2 % female) with a mean age of 14.29 years were measured during an emotional face recognition task. In addition, participants completed a self-report screening for ADHD symptoms.

RESULTS

ADHD symptoms were positively related to the HEP activity during the task in three of eight EEG sectors in the left hemisphere, as well as in all sectors in the right hemisphere.

DISCUSSION

This study is the first to demonstrate preliminary a relationship between the strength of HEP activity and ADHD symptoms in awake subjects. This finding of higher HEP amplitudes in subjects with more ADHD symptoms can be interpreted in terms of (i) increased arousal, (ii) altered neural processing of internal processes in an emotion-relevant task, and (iii) a misaligned precision-weighting process of task-irrelevant stimuli according to the predictive coding framework. These different interpretations could be reflected by previous studies showing heterogeneity of psychological deficits in individuals with ADHD symptoms. However, the generalizability to patients with diagnosed ADHD is limited due to the measurement tool for ADHD symptoms and the sample characteristics.

Habituation, Adaptation and Prediction Processes in Neurodevelopmental Disorders: A Comprehensive Review

Habituation, the simplest form of learning preserved across species and evolution, is characterized by a response decrease as a stimulus is repeated. This adaptive function has been shown to be altered in some psychiatric and neurodevelopmental disorders such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or schizophrenia. At the brain level, habituation is characterized by a decrease in neural activity as a stimulation is repeated, referred to as neural adaptation. This phenomenon influences the ability to make predictions and to detect change, two processes altered in some neurodevelopmental and psychiatric disorders. In this comprehensive review, the objectives are to characterize habituation, neural adaptation, and prediction throughout typical development and in neurodevelopmental disorders; and to evaluate their implication in symptomatology, specifically in sensitivity to change or need for sameness. A summary of the different approaches to investigate adaptation will be proposed, in which we report the contribution of animal studies as well as electrophysiological studies in humans to understanding of underlying neuronal mechanisms.

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.

The role of the salience network in cognitive and affective deficits

Analysis and interpretation of studies on cognitive and affective dysregulation often draw upon the network paradigm, especially the Triple Network Model, which consists of the default mode network (DMN), the frontoparietal network (FPN), and the salience network (SN). DMN activity is primarily dominant during cognitive leisure and self-monitoring processes. The FPN peaks during task involvement and cognitive exertion. Meanwhile, the SN serves as a dynamic "switch" between the DMN and FPN, in line with salience and cognitive demand. In the cognitive and affective domains, dysfunctions involving SN activity are connected to a broad spectrum of deficits and maladaptive behavioral patterns in a variety of clinical disorders, such as depression, insomnia, narcissism, PTSD (in the case of SN hyperactivity), chronic pain, and anxiety, high degrees of neuroticism, schizophrenia, epilepsy, autism, and neurodegenerative illnesses, bipolar disorder (in the case of SN hypoactivity). We discuss behavioral and neurological data from various research domains and present an integrated perspective indicating that these conditions can be associated with a widespread disruption in predictive coding at multiple hierarchical levels. We delineate the fundamental ideas of the brain network paradigm and contrast them with the conventional modular method in the first section of this article. Following this, we outline the interaction model of the key functional brain networks and highlight recent studies coupling SN-related dysfunctions with cognitive and affective impairments.

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

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

Little fast, little slow, should I stay or should I go? Adapting cognitive control to local-global temporal prediction across typical development

Adaptive cognitive control (CC), the ability to adjust goal-directed behavior according to changing environmental demand, can be instantiated bottom-up by implicit knowledge, including temporal predictability of task-relevant events. In S1-S2 tasks, either local (trial-by-trial hazard expectation) or global (block-by-block expectation) temporal information can induce prediction, allowing for proactive action control. Recent developmental evidence showed that adaptive CC based on global temporal prediction emerges earlier than when it is based on the local one only. However, very little is known about how children learn to dynamically adjust behavior on the fly according to changing global predictive information. Addressing this issue is nevertheless crucial to unravel the mechanisms underlying adaptive CC flexibility. Here we used a modified version of the Dynamic Temporal Prediction task to investigate how typically developing younger (6-8 years) and older children (9-11 years), adolescents (12-15 years) and adults (21-31 years) use global prediction to shape adaptive CC over time. Specifically, the short-long percentage of S2 preparatory intervals was manipulated list-wide to create a slow-fast-slow-fast fixed block sequence and test how efficiently the response speed adapted accordingly. Overall, results revealed that in all groups behavioral performance is successfully adjusted as a function of global prediction in the late phase of the task (block 3 to 4). Remarkably, only adolescents and adults exhibit an early adaptation of adaptive CC (block 1 to 2), while children younger than 11 show sluggish ability in inferring implicit changes in global predictive rules. This age-related dissociation suggests that, although being present from an early age, adaptive CC based on global predictive information needs more developmental space to become flexible in an efficient way. In the light of a neuroconstructivist approach, we suggest that bottom-up driven implicit flexibility may represent a key prerequisite for the development of efficient explicit cognitive control.

10 years of Bayesian theories of autism: A comprehensive review

Ten years ago, Pellicano and Burr published one of the most influential articles in the study of autism spectrum disorders, linking them to aberrant Bayesian inference processes in the brain. In particular, they proposed that autistic individuals are less influenced by their brains' prior beliefs about the environment. In this systematic review, we investigate if this theory is supported by the experimental evidence. To that end, we collect all studies which included comparisons across diagnostic groups or autistic traits and categorise them based on the investigated priors. Our results are highly mixed, with a slight majority of studies finding no difference in the integration of Bayesian priors. We find that priors developed during the experiments exhibited reduced influences more frequently than priors acquired previously, with various studies providing evidence for learning differences between participant groups. Finally, we focus on the methodological and computational aspects of the included studies, showing low statistical power and often inconsistent approaches. Based on our findings, we propose guidelines for future research.

Tactile sensory processing as a precursor of executive attention: Toward early detection of attention impairments and neurodevelopmental disorders

Recent studies in developmental neuroscience tend to show the existence of neural attention networks from birth. Their construction is based on the first sensory experiences that allow us to learn the patterns of the world surrounding us and preserve our limited attentional resources. Touch is the first sensory modality to develop, although it is still little studied in developmental psychology in contrast to distal modalities such as audition or vision. Atypical tactile sensory processing at an early age could predict later attention dysfunction, both of them being part of the symptomatology of neurodevelopmental disorders (NDD). We review the state of knowledge on tactile sensory processing and its links with attention, executive attention (EA) in particular, and propose that abnormal tactile sensory processing at an early age could provide markers of EA dysfunctions, contributing to the early detection of NDD. This article is categorized under: Psychology > Attention.

Ignore the glitch but mind the switch: Positive effects of methylphenidate on cognition in attention deficit hyperactivity disorder are related to prediction gain

Neuropsychological symptoms such as inattention and distractibility constitute a core characteristic of attention deficit hyperactivity disorder (ADHD). Here, we tested the hypothesis that attentional dysfunctions result from a deficit in neural gain modulation, which translates into difficulty in predictively weighting relevant sensory input while ignoring distraction. We compared thirty-seven hitherto untreated adults diagnosed with ADHD and thirty-eight healthy participants with a serial switch-drift task that requires internal models of predictable digit sequences to be either updated or stabilized. Switches between sequences that had to be indicated by key presses and digit omissions within a sequence (drifts) that should be ignored varied by stimulus-bound surprise quantified as Shannon information. To investigate whether catecholaminergic modulation by increasing extracellular norepinephrine and dopamine levels leads to an amelioration in prediction gain, participants were tested twice, with patients receiving a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, in the second session. Patients and controls differed in both updating and stabilizing, depending on the respective event surprise. Specifically, patients showed difficulty in detecting expectable switches, while having greater difficulty to ignore surprising distractions. Thus, underconfident prior beliefs in ADHD may fail to appropriately weight expected relevant input, whereas the gain of neural responses to unexpected irrelevant distractors is increased. Methylphenidate improved both flexibility and stability of prediction and had a positive effect on selective responding over time. Our results suggest that ADHD is associated with an impairment in the use of prior expectations to optimally weight sensory inputs, which is improved by increasing catecholaminergic neurotransmission.

Quantifying developmental and individual differences in spontaneous drawing completion among children

This study investigated how children's drawings can provide insights into their cognitive development. It can be challenging to quantify the diversity of children's drawings across their developmental stages as well as between individuals. This study observed children's representational drawing ability by conducting a completion task where children could freely draw on partially drawn objects, and quantitatively analyzed differences in children's drawing tendencies across age and between individuals. First, we conducted preregistered analyses, based on crowd-sourced adult ratings, to investigate the differences of drawing style with the age and autistic traits of the children, where the latter was inspired by reports of atypical drawing among children with autism spectrum disorder (ASD). Additionally, the drawings were quantified using feature representations extracted with a deep convolutional neural network (CNN), which allowed an analysis of the drawings at different perceptual levels (i.e., local or global). Findings revealed a decrease in scribbling and an increase in completion behavior with increasing age. However, no correlation between drawing behavior and autistic traits was found. The network analysis demonstrated that older children adapted to the presented stimuli in a more adult-like manner than younger children. Furthermore, ways to quantify individual differences in how children adapt to the presented stimuli are explored. Based on the predictive coding theory as a unified theory of how perception and behavior might emerge from integrating sensations and predictions, we suggest that our analyses may open up new possibilities for investigating children's cognitive development.

Differences in Prediction May Underlie Language Disorder in Autism

Language delay is often one of the first concerns of parents of toddlers with autism spectrum disorder (ASD), and early language abilities predict broader outcomes for children on the autism spectrum. Yet, mechanisms underlying language deficits in autistic children remain underspecified. One prominent component of linguistic behavior is the use of predictions or expectations during learning and processing. Several researcher teams have posited prediction deficit accounts of ASD. The basic assumption of the prediction accounts is that information is processed by making predictions and testing violations against expectations (prediction errors). Flexible (neurotypical) brains attribute differential weights to prediction errors to determine when new learning is appropriate, while autistic individuals are thought to assign disproportionate weight to prediction errors. According to some views, these prediction deficits are hypothesized to lead to higher levels of perceived novelty, resulting in “hyperplasticity” of learning based on the most recent input. In this article, we adopt the perspective that it would be useful to investigate whether language deficits in children with ASD can be attributed to atypical domain-general prediction processes.

Simulating Developmental and Individual Differences of Drawing Behavior in Children Using a Predictive Coding Model

Predictive coding has recently been proposed as a mechanistic approach to explain human perception and behavior based on the integration of perceptual stimuli (bottom-up information) and the predictions about the world based on previous experience (top-down information). However, the gap between the computational accounts of cognition and evidence of behavioral studies remains large. In this study, we used a computational model of drawing based on the mechanisms of predictive coding to systematically investigate the effects of the precision of top-down and bottom-up information when performing a drawing completion task. The results indicated that sufficient precision of both signals was required for the successful completion of the stimuli and that a reduced precision in either sensory or prediction (i.e., prior) information led to different types of atypical drawing behavior. We compared the drawings produced by our model to a dataset of drawings created by children aged between 2 and 8 years old who drew on incomplete drawings. This comparison revealed that a gradual increase in children's precision of top-down and bottom-up information as they develop effectively explains the observed change of drawing style from scribbling toward representational drawing. Furthermore, individual differences that are prevalent in children's drawings, might arise from different developmental pathways regarding the precision of these two signals. Based on these findings we propose a theory of how both general and individual development of drawing could be explained in a unified manner within the framework of predictive coding.

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

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

Toward a Multidimensional Understanding of Misophonia Using Cluster-Based Phenotyping

Misophonia is a condition characterized by hypersensitivity and strong emotional reactivity to specific auditory stimuli. Misophonia clinical presentations are relatively complex and reflect individualized experiences across clinical populations. Like some overlapping neurodevelopmental and neuropsychiatric disorders, misophonia is potentially syndromic where symptom patterns rather than any one symptom contribute to diagnosis. The current study conducted an exploratory k-means cluster analysis to evaluate symptom presentation in a non-clinical sample of young adult undergraduate students (N = 343). Individuals participated in a self-report spectrum characteristics survey indexing misophonia, tinnitus severity, sensory hypersensitivity, and social and psychiatric symptoms. Results supported a three-cluster solution that split participants on symptom presentation: cluster 1 presented with more severe misophonia symptoms but few overlapping formally diagnosed psychiatric co-occurring conditions; cluster 3 was characterized by a more nuanced clinical presentation of misophonia with broad-band sensory hypersensitivities, tinnitus, and increased incidence of social processing and psychiatric symptoms, and cluster 2 was relatively unaffected by misophonia or other sensitivities. Clustering results illustrate the spectrum characteristics of misophonia where symptom patterns range from more “pure” form misophonia to presentations that involve more broad-range sensory-related and psychiatric symptoms. Subgroups of individuals with misophonia may characterize differential neuropsychiatric risk patterns and stem from potentially different causative factors, highlighting the importance of exploring misophonia as a multidimensional condition of complex etiology.

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

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

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

Background

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

Objective

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

Methods

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

Results

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

Conclusion

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

Auditory Event Related Potentials in children with autism spectrum disorder

OBJECTIVE

To analyze auditory cortical processing in high functioning ASD individuals.

METHODS

Thirty individuals were included in the study (15 with Autism Spectrum Disorder and 15 with typical development), and their Auditory Event Related Potentials evaluation, elicited with tone burst and speech stimuli, were analyzed.

RESULTS

There were no significant differences between individuals with high-functioning Autism Spectrum Disorder without intellectual disability and those with typical development in the auditory Event-related Potentials elicited with tone bursts or speech stimuli.

CONCLUSIONS

The results of Auditory Event Related Potentials did not show any change at the cortical level in individuals with Autism Spectrum Disorder.

Decoding expectation and surprise in dementia: the paradigm of music

Making predictions about the world and responding appropriately to unexpected events are essential functions of the healthy brain. In neurodegenerative disorders, such as frontotemporal dementia and Alzheimer's disease, impaired processing of 'surprise' may underpin a diverse array of symptoms, particularly abnormalities of social and emotional behaviour, but is challenging to characterize. Here, we addressed this issue using a novel paradigm: music. We studied 62 patients (24 female; aged 53-88) representing major syndromes of frontotemporal dementia (behavioural variant, semantic variant primary progressive aphasia, non-fluent-agrammatic variant primary progressive aphasia) and typical amnestic Alzheimer's disease, in relation to 33 healthy controls (18 female; aged 54-78). Participants heard famous melodies containing no deviants or one of three types of deviant note-acoustic (white-noise burst), syntactic (key-violating pitch change) or semantic (key-preserving pitch change). Using a regression model that took elementary perceptual, executive and musical competence into account, we assessed accuracy detecting melodic deviants and simultaneously recorded pupillary responses and related these to deviant surprise value (information-content) and carrier melody predictability (entropy), calculated using an unsupervised machine learning model of music. Neuroanatomical associations of deviant detection accuracy and coupling of detection to deviant surprise value were assessed using voxel-based morphometry of patients' brain MRI. Whereas Alzheimer's disease was associated with normal deviant detection accuracy, behavioural and semantic variant frontotemporal dementia syndromes were associated with strikingly similar profiles of impaired syntactic and semantic deviant detection accuracy and impaired behavioural and autonomic sensitivity to deviant information-content (all P < 0.05). On the other hand, non-fluent-agrammatic primary progressive aphasia was associated with generalized impairment of deviant discriminability (P < 0.05) due to excessive false-alarms, despite retained behavioural and autonomic sensitivity to deviant information-content and melody predictability. Across the patient cohort, grey matter correlates of acoustic deviant detection accuracy were identified in precuneus, mid and mesial temporal regions; correlates of syntactic deviant detection accuracy and information-content processing, in inferior frontal and anterior temporal cortices, putamen and nucleus accumbens; and a common correlate of musical salience coding in supplementary motor area (all P < 0.05, corrected for multiple comparisons in pre-specified regions of interest). Our findings suggest that major dementias have distinct profiles of sensory 'surprise' processing, as instantiated in music. Music may be a useful and informative paradigm for probing the predictive decoding of complex sensory environments in neurodegenerative proteinopathies, with implications for understanding and measuring the core pathophysiology of these diseases.

The Latin America and the Caribbean Consortium on Dementia (LAC-CD): From Networking to Research to Implementation Science

In comparison with other regions, dementia prevalence in Latin America is growing rapidly, along with the consequent clinical, social, and economic burden upon patients and their families. The combination of fragile health care systems, large social inequalities, and isolated clinical and research initiatives makes the coordination of efforts imperative. The Latin America and the Caribbean Consortium on Dementia (LAC-CD) is a regional organization overseeing and promoting clinical and research activities on dementia. Here, we first provide an overview of the consortium, highlighting the antecedents and current mission. Then, we present the consortium’s regional research, including the multi-partner consortium to expand dementia research in Latin America (ReDLat), which aims to identify the unique genetic, social, and economic factors that drive Alzheimer’s and frontotemporal dementia presentation in LAC relative to the US. We describe an extension of ReDLat which aims to develop affordable markers of disease subtype and severity using high density EEG. We introduce current initiatives promoting regional diagnosis, visibility, and capacity, including the forthcoming launch of the Latin American Brain Health Institute (BrainLat). We discuss LAC-CD-led advances in brain health diplomacy, including an assessment of responses to the impact of COVID-19 on people with dementia and examining the knowledge of public policies among experts in the region. Finally, we present the current knowledge-to-action framework, which paves the way for a future regional action plan. Coordinated actions are crucial to forging strong regional bonds, supporting the implementation of regional dementia plans, improving health systems, and expanding research collaborations across Latin America.

Cortical auditory evoked potentials in autism spectrum disorder: a systematic review

PURPOSE

To identify and analyze what are the characteristic findings of Cortical Auditory Evoked Potentials (CAEP) in children and / or adolescents with Autism Spectrum Disorder (ASD) compared to typical development, through a systematic literature review.

RESEARCH STRATEGIES

Based on the formulation of a research question, a bibliographic survey was carried out in seven databases (Web of Science, Pubmed, Cochrane Library, Lilacs, Scielo, Science Direct, and Google Sholar), with the following descriptors: autism spectrum disorder (transtorno do espectro autista), autistic disorder (transtorno autístico), evoked potentials, auditory (potenciais evocados auditivos), event related potentials, P300 (potencial evocado P300) e child (criança). This review was registered in Prospero, under number 118751.

SELECTION CRITERIA

Were selected articles published, without language limitation, between 2007 and 2019.

DATA ANALYSIS

The characteristics of the latency and amplitude aspects of the P1, N1, P2, N2 and P3 components present in the CAEP.

RESULTS

193 studies were located; however, 15 original articles were included the inclusion criteria for this study. Although it has not been possible to identify any pattern of response for the P1, N1, P2 and N2 components, the results of the selected studies have demonstrated that individuals with ASD may present a decrease in amplitude and increase in latency of the P3 component.

CONCLUSION

Individuals with ASD may present different responses to the components of the CAEP, and the decrease of the amplitude and increase of the latency of the P3 component were the most common characteristics.

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

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

Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway

Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.

The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science

Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent.

Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder

Neurodevelopmental disorders are characterized by heterogeneous and non-specific nature of their clinical symptoms. In particular, hyper- and hypo-reactivity to sensory stimuli are diagnostic features of autism spectrum disorder and are reported across many neurodevelopmental disorders. However, computational mechanisms underlying the unusual paradoxical behaviors remain unclear. In this study, using a robot controlled by a hierarchical recurrent neural network model with predictive processing and learning mechanism, we simulated how functional disconnection altered the learning process and subsequent behavioral reactivity to environmental change. The results show that, through the learning process, long-range functional disconnection between distinct network levels could simultaneously lower the precision of sensory information and higher-level prediction. The alteration caused a robot to exhibit sensory-dominated and sensory-ignoring behaviors ascribed to sensory hyper- and hypo-reactivity, respectively. As long-range functional disconnection became more severe, a frequency shift from hyporeactivity to hyperreactivity was observed, paralleling an early sign of autism spectrum disorder. Furthermore, local functional disconnection at the level of sensory processing similarly induced hyporeactivity due to low sensory precision. These findings suggest a computational explanation for paradoxical sensory behaviors in neurodevelopmental disorders, such as coexisting hyper- and hypo-reactivity to sensory stimulus. A neurorobotics approach may be useful for bridging various levels of understanding in neurodevelopmental disorders and providing insights into mechanisms underlying complex clinical symptoms.

Visual statistical learning and integration of perceptual priors are intact in attention deficit hyperactivity disorder

Background

Deficits in visual statistical learning and predictive processing could in principle explain the key characteristics of inattention and distractibility in attention deficit hyperactivity disorder (ADHD). Specifically, from a Bayesian perspective, ADHD may be associated with flatter likelihoods (increased sensory processing noise), and/or difficulties in generating or using predictions. To our knowledge, such hypotheses have never been directly tested.

Methods

We here test these hypotheses by evaluating whether adults diagnosed with ADHD (n = 17) differed from a control group (n = 30) in implicitly learning and using low-level perceptual priors to guide sensory processing. We used a visual statistical learning task in which participants had to estimate the direction of a cloud of coherently moving dots. Unbeknown to the participants, two of the directions were more frequently presented than the others, creating an implicit bias (prior) towards those directions. This task had previously revealed differences in other neurodevelopmental disorders, such as autistic spectrum disorder and schizophrenia.

Results

We found that both groups acquired the prior expectation for the most frequent directions and that these expectations substantially influenced task performance. Overall, there were no group differences in how much the priors influenced performance. However, subtle group differences were found in the influence of the prior over time.

Conclusion

Our findings suggest that the symptoms of inattention and hyperactivity in ADHD do not stem from broad difficulties in developing and/or using low-level perceptual priors.

Individuals With Autism Have No Detectable Deficit in Neural Markers of Prediction Error When Presented With Auditory Rhythms of Varied Temporal Complexity

The brain's ability to encode temporal patterns and predict upcoming events is critical for speech perception and other aspects of social communication. Deficits in predictive coding may contribute to difficulties with social communication and overreliance on repetitive predictable environments in individuals with autism spectrum disorder (ASD). Using a mismatch negativity (MMN) task involving rhythmic tone sequences of varying complexity, we tested the hypotheses that (1) individuals with ASD have reduced MMN response to auditory stimuli that deviate in presentation timing from expected patterns, particularly as pattern complexity increases and (2) amplitude of MMN signal is inversely correlated with level of impairment in social communication and repetitive behaviors. Electroencephalography was acquired as individuals (age 6-21 years) listened to repeated five-rhythm tones that varied in the Shannon entropy of the rhythm across three conditions (zero, medium-1 bit, and high-2 bit entropy). The majority of the tones conformed to the established rhythm (standard tones); occasionally the fourth tone was temporally shifted relative to its expected time of occurrence (deviant tones). Social communication and repetitive behaviors were measured using the Social Responsiveness Scale and Repetitive Behavior Scale-Revised. Both neurotypical controls (n = 19) and individuals with ASD (n = 21) show stepwise decreases in MMN as a function of increasing entropy. Contrary to the result forecasted by a predictive coding hypothesis, individuals with ASD do not differ from controls in these neural mechanisms of prediction error to auditory rhythms of varied temporal complexity, and there is no relationship between these signals and social communication or repetitive behavior measures. LAY SUMMARY: We tested the idea that the brain's ability to use previous experience to influence processing of sounds is weaker in individuals with autism spectrum disorder (ASD) than in neurotypical individuals. We found no difference between individuals with ASD and neurotypical controls in brain wave responses to sounds that occurred earlier than expected in either simple or complex rhythms. There was also no relationship between these brain waves and social communication or repetitive behavior scores.

Examining the Temporal Limits of Enhanced Visual Feature Detection in Children With Autism

The enhanced perceptual processing of visual features in children with autism spectrum disorder (ASD) is supported by an abundance of evidence in the spatial domain, with less robust evidence regarding whether this extends to information presented across time. The current study aimed to replicate and extend previous work finding that children with an ASD demonstrated enhanced perceptual accuracy in detecting feature-based (but not categorically defined) targets in time, when these were presented quickly, at a stimulus onset asynchrony (SOA) of 50 ms per item. Specifically, we extend the range of SOAs to examine the temporal boundaries of this enhanced accuracy and examine whether there is a relationship between ASD-related traits and detection accuracy on temporal visual search tasks. Individuals with autism perceived feature-based targets with statistically higher accuracy than their typically developing peers between SOAs of 39 and 65 ms and were numerically faster at all SOAs. No group differences were noted for category-based task accuracy. Our results also demonstrated that ASD-related traits measured by the autism spectrum quotient were positively correlated with accuracy on the feature-based task. Overall, results suggest that accurate visual perception of features (particularly color) is enhanced in children with ASD across time. LAY SUMMARY: Our results suggest that children with autism are able to process visual features, such as color, more accurately than typically developing children, even when these are presented very rapidly. Accuracy was higher in children with higher levels of autism-related traits and symptoms. Our findings suggest that more accurate visual perception exists not only across space in children with autism, as much of the existing literature demonstrates, but also over time. Autism Res 2020, 13: 1561-1572. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Dynamic neurocognitive changes in interoception after heart transplant

Heart–brain integration dynamics are critical for interoception (i.e. the sensing of body signals). In this unprecedented longitudinal study, we assessed neurocognitive markers of interoception in patients who underwent orthotopic heart transplants and matched healthy controls. Patients were assessed longitudinally before surgery (T1), a few months later (T2) and a year after (T3). We assessed behavioural (heartbeat detection) and electrophysiological (heartbeat evoked potential) markers of interoception. Heartbeat detection task revealed that pre-surgery (T1) interoception was similar between patients and controls. However, patients were outperformed by controls after heart transplant (T2), but no such differences were observed in the follow-up analysis (T3). Neurophysiologically, although heartbeat evoked potential analyses revealed no differences between groups before the surgery (T1), reduced amplitudes of this event-related potential were found for the patients in the two post-transplant stages (T2, T3). All these significant effects persisted after covariation with different cardiological measures. In sum, this study brings new insights into the adaptive properties of brain–heart pathways.

Increased variability but intact integration during visual navigation in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects' dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants' beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.

The developing predictive brain: How implicit temporal expectancy induced by local and global prediction shapes action preparation across development

Human behavior is continuously shaped not just as a function of explicitly responding to external world events but also by internal biases implicitly driven by the capacity to extract statistics from complex sensory patterns. Two possible sources of predictability engaged to generate and update temporal expectancy are the implicit extraction of either local or global statistical contingencies in the events' temporal structure. In the context of action preparation the local prediction has been reported to be stable from the age of 6. However, there is no evidence about how the ability to extract and use global statistical patterns to establish temporal expectancy changes across development. Here we used a new, child-friendly reaction time task purposely designed to investigate how local (within-trial expectancy bias) and global (between-block expectancy bias) prediction interplay to generate temporal expectancy and consequently shape action preparation in young (5- to 6-year-old), middle-aged (7- to 8-year-old) and old (9- to 10-year-old) typically developing children. We found that while local temporal prediction showed stable developmental trajectories, the ability to use a global rule to action preparation in terms of both accuracy and speed becomes stable after the age of seven. These findings are discussed by adopting a neuroconstructivist-inspired theoretical account, according to which the developmental constraints on learning from hierarchically nested levels of sensory complexity may constitute a necessary prerequisite for mastering complex domains.

Homogeneous Intrinsic Neuronal Excitability Induces Overfitting to Sensory Noise: A Robot Model of Neurodevelopmental Disorder

Neurodevelopmental disorders, including autism spectrum disorder, have been intensively investigated at the neural, cognitive, and behavioral levels, but the accumulated knowledge remains fragmented. In particular, developmental learning aspects of symptoms and interactions with the physical environment remain largely unexplored in computational modeling studies, although a leading computational theory has posited associations between psychiatric symptoms and an unusual estimation of information uncertainty (precision), which is an essential aspect of the real world and is estimated through learning processes. Here, we propose a mechanistic explanation that unifies the disparate observations via a hierarchical predictive coding and developmental learning framework, which is demonstrated in experiments using a neural network-controlled robot. The results show that, through the developmental learning process, homogeneous intrinsic neuronal excitability at the neural level induced via self-organization changes at the information processing level, such as hyper sensory precision and overfitting to sensory noise. These changes led to multifaceted alterations at the behavioral level, such as inflexibility, reduced generalization, and motor clumsiness. In addition, these behavioral alterations were accompanied by fluctuating neural activity and excessive development of synaptic connections. These findings might bridge various levels of understandings in autism spectrum and other neurodevelopmental disorders and provide insights into the disease processes underlying observed behaviors and brain activities in individual patients. This study shows the potential of neurorobotics frameworks for modeling how psychiatric disorders arise from dynamic interactions among the brain, body, and uncertain environments.

Phasic locus coeruleus activity regulates cortical encoding of salience information

Phasic activation of locus coeruleus (LC)-norepinephrine (NE) neurons is associated with focused attention and behavioral responses to salient stimuli. We used cell-type-specific optogenetics and single-unit neurophysiology to identify how LC activity influences neural encoding of sensory information. We found that phasic, but not tonic, LC-NE photoactivation generated a distinct event-related potential (ERP) across cortical regions. Salient sensory stimuli (which innately trigger phasic LC activity) produced strong excitatory cortical responses during this ERP window. Application of weaker, nonsalient stimuli produced limited responses, but these responses were elevated to salient stimulus levels when they were temporally locked with phasic LC photoactivation. These results demonstrate that phasic LC activity enhances cortical encoding of salient stimuli by facilitating long-latency signals within target regions in response to stimulus intensity/salience. The LC-driven salience signal identified here provides a measure of phasic LC activity that can be used to investigate the LC's role in attentional processing across species.

Interpersonal Synchronization, Motor Coordination, and Control Are Impaired During a Dynamic Imitation Task in Children With Autism Spectrum Disorder

Background: Impairments in imitation abilities have been commonly described in children with autism spectrum disorder (ASD). How motricity in interpersonal coordination impacts imitation, during long lasting semi-ecological conditions, has not been carefully investigated.

Methods: Eighty-five children and adolescents (39 controls with typical development, TD; 29 patients with ASD; 17 patients with developmental coordination disorder, DCD), aged 6 to 20 years, participated to a behavioral paradigm in which participants, standing and moving, interacted with a virtual tightrope walker standing and moving as well. During the protocol, we measured automatically and continuously bodily postures and movements from RGB sensor recording to assess participants' behavioral imitation.

Results: We show that (1) interpersonal synchronization (as evidenced by the synchrony between the participant's and the tightrope walker's bars) and (2) motor coordination (as evidenced by the synchrony between the participant's bar and its own head axis) increased with age and were more impaired in patients with ASD. Also, motor control as evidenced by the movement angle standard deviations of participants' bar and head were significantly impaired in ASD compared to TD or DCD.

Conclusion: Interpersonal synchronization and motor coordination during ecological interaction show both subtle impairment in children with ASD as compared to children with TD or DCD. These results questioned how motricity mature in terms of motor control and proprioception in children with ASD.

Altered neural signatures of interoception in multiple sclerosis

Multiple sclerosis (MS) patients present several alterations related to sensing of bodily signals. However, no specific neurocognitive impairment has yet been proposed as a core deficit underlying such symptoms. We aimed to determine whether MS patients present changes in interoception-that is, the monitoring of autonomic bodily information-a process that might be related to various bodily dysfunctions. We performed two studies in 34 relapsing-remitting, early-stage MS patients and 46 controls matched for gender, age, and education. In Study 1, we evaluated the heartbeat-evoked potential (HEP), a cortical signature of interoception, via a 128-channel EEG system during a heartbeat detection task including an exteroceptive and an interoceptive condition. Then, we obtained whole-brain MRI recordings. In Study 2, participants underwent fMRI recordings during two resting-state conditions: mind wandering and interoception. In Study 1, controls exhibited greater HEP modulation during the interoceptive condition than the exteroceptive one, but no systematic differences between conditions emerged in MS patients. Patients presented atrophy in the left insula, the posterior part of the right insula, and the right anterior cingulate cortex, with abnormal associations between neurophysiological and neuroanatomical patterns. In Study 2, controls showed higher functional connectivity and degree for the interoceptive state compared with mind wandering; however, this pattern was absent in patients, who nonetheless presented greater connectivity and degree than controls during mind wandering. MS patients were characterized by atypical multimodal brain signatures of interoception. This finding opens a new agenda to examine the role of inner-signal monitoring in the body symptomatology of MS.

Autism spectrum disorders: a meta-analysis of executive function

Evidence of executive dysfunction in autism spectrum disorders (ASD) across development remains mixed and establishing its role is critical for guiding diagnosis and intervention. The primary objectives of this meta-analysis is to analyse executive function (EF) performance in ASD, the fractionation across EF subdomains, the clinical utility of EF measures and the influence of multiple moderators (for example, age, gender, diagnosis, measure characteristics). The Embase, Medline and PsychINFO databases were searched to identify peer-reviewed studies published since the inclusion of Autism in DSM-III (1980) up to end of June 2016 that compared EF in ASD with neurotypical controls. A random-effects model was used and moderators were tested using subgroup analysis. The primary outcome measure was Hedges' g effect size for EF and moderator factors. Clinical sensitivity was determined by the overlap percentage statistic (OL%). Results were reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 235 studies comprising 14 081 participants were included (N, ASD=6816, Control=7265). A moderate overall effect size for reduced EF (Hedges' g=0.48, 95% confidence interval (CI) 0.43-0.53) was found with similar effect sizes across each domain. The majority of moderator comparisons were not significant although the overall effect of executive dysfunction has gradually reduced since the introduction of ASD. Only a small number of EF measures achieved clinical sensitivity. This study confirms a broad executive dysfunction in ASD that is relatively stable across development. The fractionation of executive dysfunction into individual subdomains was not supported, nor was diagnostic sensitivity. Development of feasible EF measures focussing on clinical sensitivity for diagnosis and treatment studies should be a priority.

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

BACKGROUND

Recent predictive coding accounts of autism spectrum disorder (ASD) suggest that a key deficit in ASD concerns the inflexibility in modulating local prediction errors as a function of global top-down expectations. As a direct test of this central hypothesis, we used electroencephalography to investigate whether local prediction error processing was less modulated by global context (i.e., global stimulus frequency) in ASD.

METHODS

A group of 18 adults with ASD was compared with a group of 24 typically developed adults on a well-validated hierarchical auditory oddball task in which participants listened to short sequences of either five identical sounds (local standard) or four identical sounds and a fifth deviant sound (local deviant). The latter condition is known to generate the mismatch negativity (MMN) component, believed to reflect early sensory prediction error processing. Crucially, previous studies have shown that in blocks with a higher frequency of local deviant sequences, top-down expectations seem to attenuate the MMN. We predicted that this modulation by global context would be less pronounced in the ASD group.

RESULTS

Both groups showed an MMN that was modulated by global context. However, this effect was smaller in the ASD group as compared with the typically developed group. In contrast, the P3b, as an electroencephalographic marker of conscious expectation processes, did not differ across groups.

CONCLUSIONS

Our results demonstrate that people with ASD are less flexible in modulating their local predictions (reflected in MMN), thereby confirming the central hypothesis of contemporary predictive coding accounts of ASD.

Social neuroscience: undoing the schism between neurology and psychiatry

Multiple disorders once jointly conceived as "nervous diseases" became segregated by the distinct institutional traditions forged in neurology and psychiatry. As a result, each field specialized in the study and treatment of a subset of such conditions. Here we propose new avenues for interdisciplinary interaction through a triangulation of both fields with social neuroscience. To this end, we review evidence from five relevant domains (facial emotion recognition, empathy, theory of mind, moral cognition, and social context assessment), highlighting their common disturbances across neurological and psychiatric conditions and discussing their multiple pathophysiological mechanisms. Our proposal is anchored in multidimensional evidence, including behavioral, neurocognitive, and genetic findings. From a clinical perspective, this work paves the way for dimensional and transdiagnostic approaches, new pharmacological treatments, and educational innovations rooted in a combined neuropsychiatric training. Research-wise, it fosters new models of the social brain and a novel platform to explore the interplay of cognitive and social functions. Finally, we identify new challenges for this synergistic framework.

Your perspective and my benefit: multiple lesion models of self-other integration strategies during social bargaining

Recursive social decision-making requires the use of flexible, context-sensitive long-term strategies for negotiation. To succeed in social bargaining, participants' own perspectives must be dynamically integrated with those of interactors to maximize self-benefits and adapt to the other's preferences, respectively. This is a prerequisite to develop a successful long-term self-other integration strategy. While such form of strategic interaction is critical to social decision-making, little is known about its neurocognitive correlates. To bridge this gap, we analysed social bargaining behaviour in relation to its structural neural correlates, ongoing brain dynamics (oscillations and related source space), and functional connectivity signatures in healthy subjects and patients offering contrastive lesion models of neurodegeneration and focal stroke: behavioural variant frontotemporal dementia, Alzheimer's disease, and frontal lesions. All groups showed preserved basic bargaining indexes. However, impaired self-other integration strategy was found in patients with behavioural variant frontotemporal dementia and frontal lesions, suggesting that social bargaining critically depends on the integrity of prefrontal regions. Also, associations between behavioural performance and data from voxel-based morphometry and voxel-based lesion-symptom mapping revealed a critical role of prefrontal regions in value integration and strategic decisions for self-other integration strategy. Furthermore, as shown by measures of brain dynamics and related sources during the task, the self-other integration strategy was predicted by brain anticipatory activity (alpha/beta oscillations with sources in frontotemporal regions) associated with expectations about others' decisions. This pattern was reduced in all clinical groups, with greater impairments in behavioural variant frontotemporal dementia and frontal lesions than Alzheimer's disease. Finally, connectivity analysis from functional magnetic resonance imaging evidenced a fronto-temporo-parietal network involved in successful self-other integration strategy, with selective compromise of long-distance connections in frontal disorders. In sum, this work provides unprecedented evidence of convergent behavioural and neurocognitive signatures of strategic social bargaining in different lesion models. Our findings offer new insights into the critical roles of prefrontal hubs and associated temporo-parietal networks for strategic social negotiation.

A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder

The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions-predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down predictions or an enhanced weighting of bottom-up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process.

A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder

The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions-predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down predictions or an enhanced weighting of bottom-up prediction errors. Likewise, autism has been explained in terms of similar perturbations. We suggest that this theoretical overlap may explain overlapping symptomatology. Experimental evidence highlights meaningful distinctions and consistencies between these disorders. We hypothesize individuals with ASD may experience some degree of delusions without the presence of any additional impairment, but that hallucinations are likely indicative of a distinct process.