When 2 become 1: Autistic simultaneity judgements about asynchronous audiovisual speech

It has been proposed that autistic people experience a temporal distortion whereby the temporal binding window of multisensory integration is extended. Research to date has focused on autistic children so whether these differences persist into adulthood remains unknown. In addition, the possibility that the previous observations have arisen from between-group differences in response bias, rather than perceptual differences, has not been addressed. Participants completed simultaneity judgements of audiovisual speech stimuli across a range of stimulus-onset asynchronies. Response times and accuracy data were fitted to a drift-diffusion model so that the drift rate (a measure of processing efficiency) and starting point (response bias) could be estimated. In Experiment 1, we tested a sample of non-autistic adults who completed the Autism Quotient questionnaire. Autism Quotient score was not correlated with either drift rate or response bias, nor were there between-group differences when splitting based on the first and third quantiles of scores. In Experiment 2, we compared the performance of autistic with a group of non-autistic adults. There were no between-group differences in either drift rate or starting point. The results of this study do not support the previous suggestion that autistic people have an extended temporal binding window for audiovisual speech. In addition, exploratory analysis revealed that operationalising the temporal binding window in different ways influenced whether a group difference was observed, which is an important consideration for future work.

Visual processing and decision-making in autism and dyslexia: Insights from cross-syndrome approaches

Atypical visual processing has been reported in developmental conditions like autism and dyslexia, and some accounts propose a causal role for visual processing in the development of these conditions. However, few studies make direct comparisons between conditions, or use sufficiently sensitive methods, meaning that it is hard to say whether atypical visual processing tells us anything specific about these conditions, or whether it reflects a more general marker of atypical development. Here I review findings from two computational modelling approaches (equivalent noise and diffusion modelling) and related electroencephalography (EEG) indices which we have applied to data from autistic, dyslexic and typically developing children to reveal how the component processes involved in visual processing and decision-making are altered in autism and dyslexia. The results identify both areas of convergence and divergence in autistic and dyslexic children's visual processing and decision-making, with implications for influential theoretical accounts such as weak central coherence, increased internal noise, and dorsal-stream vulnerability. In both sets of studies, we also see considerable variability across children in all three groups. To better understand this variability, and further understand the convergence and divergence identified between conditions, future studies would benefit from studying how the component processes reviewed here relate to transdiagnostic dimensions, which will also give insights into individual differences in visual processing and decision-making more generally.

Decision-making in autism: A narrative review

LAY SUMMARY

Many autistic people report difficulties with real-life decision-making. However, when doing decision-making tests in laboratory experiments, autistic people often perform as well or better than non-autistic people. We review previously published studies on autistic people's decision-making, across different types of tests, to understand what type of decision-making is more challenging. To do this, we searched four databases of research papers. We found 104 studies that tested, in total, 2712 autistic and 3189 comparison participants on different decision-making tasks. We found that there were four categories of decision-making tests that were used in these experiments: perceptual (e.g. deciding which image has the most dots); reward learning (e.g. learning which deck of cards gives the best reward); metacognition (e.g. knowing how well you perform or what you want); and value-based (e.g. making a decision based on a choice between two outcomes that differ in value to you). Overall, these studies suggest that autistic and comparison participants tend to perform similarly well at perceptual and reward-learning decisions. However, autistic participants tended to decide differently from comparison participants on metacognition and value-based paradigms. This suggests that autistic people might differ from typically developing controls in how they evaluate their own performance and in how they make decisions based on weighing up the subjective value of two different options. We suggest these reflect more general differences in metacognition, thinking about thinking, in autism.

Developmental Language Disorder Is Associated With Slower Processing Across Domains: A Meta-Analysis of Time-Based Tasks

PURPOSE

Individuals with developmental language disorder (DLD) often exhibit slower processing on time-based tasks in comparison with age-matched peers. Processing speed has been linked to various linguistic skills and might serve as a global indicator of individual differences in language abilities. Despite an extensive literature on processing speed in DLD, it remains unclear whether slower processing is domain general or restricted to linguistic and/or auditory tasks.

METHOD

This meta-analysis used robust variance estimation to compare response/reaction times (RTs) of DLD and age-matched groups (N = 812 DLD, 870 neurotypical; M _age [DLD] = 8.9 years, range: 4.3-22.7 years). Moderators included task (simple RT, choice RT, naming, congruent/baseline conditions of interference control tasks), stimulus type (linguistic/nonlinguistic), stimulus modality (auditory/nonauditory), and response modality (verbal/nonverbal). Age and publication year were covariates.

RESULTS

The overall effect based on 46 studies and 144 estimates indicated longer mean RTs in DLD groups (g = .47, p < .001, 95% CI [.38, .55]). Moderator analyses indicated larger effects when tasks required verbal as opposed to nonverbal responses. No other moderators approached significance. All subgroup analyses were significant, indicating longer mean RTs in DLD groups across tasks, stimulus types, stimulus modalities, and response modalities.

CONCLUSIONS

Individuals with DLD exhibit longer RTs across verbal and nonverbal tasks, which may contribute to observed difficulties in language, motor skills, and executive functioning. Simple processing speed measures should be included in screening for language delays but may not be suitable for differential diagnosis, given that slower processing may occur across multiple disorders.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21809355.

Space- and feature-based attention operate both independently and interactively within latent components of perceptual decision making

Top-down visual attention filters undesired stimuli while selected information is afforded the lion's share of limited cognitive resources. Multiple selection mechanisms can be deployed simultaneously, but how unique influences of each combine to facilitate behavior remains unclear. Previously, we failed to observe an additive perceptual benefit when both space-based attention (SBA) and feature-based attention (FBA) were cued in a sparse display (Liang & Scolari, 2020): FBA was restricted to higher order decision-making processes when combined with a valid spatial cue, whereas SBA additionally facilitated target enhancement. Here, we introduced a series of design modifications across three experiments to elicit both attention mechanisms within signal enhancement while also investigating the impacts on decision making. First, we found that when highly reliable spatial and feature cues made unique contributions to search (experiment 1), or when each cue component was moderately reliable (experiments 2a and 2b), both mechanisms were deployed independently to resolve the target. However, the same manipulations produced interactive attention effects within other latent decision-making components that depended on the probability of the integrated cueing object. Time spent before evidence accumulation was reduced and responses were more conservative for the most likely pre-cue combination-even when it included an invalid component. These data indicate that selection mechanisms operate on sensory signals invariably in an independent manner, whereas a higher-order dependency occurs outside of signal enhancement.

Unraveling the cognitive correlates of heart rate variability with the drift diffusion model

The Neurovisceral Integration Model posits a link between resting vagally mediated heart rate variability (vmHRV) and cognitive control. Empirical support for this link is mixed, potentially due to coarse performance metrics such as mean response time (RT). To clarify this issue, we tested the relationships between resting vmHRV and refined estimates of cognitive control- as revealed by the ex-Gaussian model of RT and, to a greater extent, the drift diffusion model (DDM, a computational model of two-choice performance). Participants (N = 174) completed a five-minute resting baseline while ECG was collected followed by a Simon spatial conflict task. The root mean square of successive differences in interbeat intervals was calculated to index resting vmHRV. Resting vmHRV was unrelated to Simon's mean RT and accuracy rates, but was inversely related to the ex-Gaussian parameter reflecting slow RTs (tau); however, this finding was attenuated after adjustment for covariates. High resting vmHRV was related to faster drift rates and slower non-decision times, DDM parameters reflecting goal-directed cognition and sensorimotor processes, respectively. The DDM effects survived covariate adjustment and were specific to incongruent trials (i.e., when cognitive control demands were high). Findings suggest a link between vmHRV and cognitive control vis-a-vis drift rate, and potentially, a link between vmHRV and motoric inhibition vis-a-vis non-decision time. These cognitive correlates would have been missed with reliance on traditional performance. Findings are discussed with respect to the inhibitory processes that promote effective performance in high vmHRV individuals.

Sensory Perception in Autism: What Can We Learn?

Autism is a neurodevelopmental disorder of unknown etiology. Recently, there has been a growing interest in sensory processing in autism as a core phenotype. However, basic questions remain unanswered. Here, we review the major findings and models of perception in autism and point to methodological issues that have led to conflicting results. We show that popular models of perception in autism, such as the reduced prior hypothesis, cannot explain the many and varied findings. To resolve these issues, we point to the benefits of using rigorous psychophysical methods to study perception in autism. We advocate for perceptual models that provide a detailed explanation of behavior while also taking into account factors such as context, learning, and attention. Furthermore, we demonstrate the importance of tracking changes over the course of development to reveal the causal pathways and compensatory mechanisms. Finally, we propose a developmental perceptual narrowing account of the condition. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks

Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks. We tested these hypotheses using hierarchical Bayesian diffusion models with a rigorous blind modelling approach, finding no conclusive evidence for our hypotheses. Using a data-driven method, we identified a response-locked centro-parietal component previously linked to the decision-making process. The build-up in this component did not consistently relate to evidence accumulation in autistic children. This suggests that the relationship between the EEG measure and diffusion-modelling is not straightforward in autistic children. Compared to a related study of children with dyslexia, motion processing differences appear less pronounced in autistic children. Exploratory analyses also suggest weak evidence that ADHD symptoms moderate perceptual decision-making in autistic children.

Neural Substrates of the Drift-Diffusion Model in Brain Disorders

Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different DDM parameters on several brain areas, including the cortex and basal ganglia. Furthermore, we discuss the changes in DDM parameters due to structural and functional impairments in several clinical disorders, including Parkinson's disease, Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive-Compulsive Disorder (OCD), and schizophrenia. This review thus uses DDM to provide a theoretical understanding of different brain disorders.

Raising the bar: improving methodological rigour in cognitive alcohol research

BACKGROUND AND AIMS

A range of experimental paradigms claim to measure the cognitive processes underpinning alcohol use, suggesting that heightened attentional bias, greater approach tendencies and reduced cue-specific inhibitory control are important drivers of consumption. This paper identifies methodological shortcomings within this broad domain of research and exemplifies them in studies focused specifically on alcohol-related attentional bias.

ARGUMENT AND ANALYSIS

We highlight five main methodological issues: (i) the use of inappropriately matched control stimuli; (ii) opacity of stimulus selection and validation procedures; (iii) a credence in noisy measures; (iv) a reliance on unreliable tasks; and (v) variability in design and analysis. This is evidenced through a review of alcohol-related attentional bias (64 empirical articles, 68 tasks), which reveals the following: only 53% of tasks use appropriately matched control stimuli; as few as 38% report their stimulus selection and 19% their validation procedures; less than 28% used indices capable of disambiguating attentional processes; 22% assess reliability; and under 2% of studies were pre-registered.

CONCLUSIONS

Well-matched and validated experimental stimuli, the development of reliable cognitive tasks and explicit assessment of their psychometric properties, and careful consideration of behavioural indices and their analysis will improve the methodological rigour of cognitive alcohol research. Open science principles can facilitate replication and reproducibility in alcohol research.

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.

High spatial frequency filtered primes hastens happy faces categorization in autistic adults

Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging, and might be related to alterations in LSF predictive processes. We analyzed the data of 27 autistic and 34 non autistic (NA) adults on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs.LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face compared to HSF primes, in the NA group but not in autism. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups. Moreover, the advantage of HSF vs.LSF primes was stronger for angry than happy faces in NA, but was stronger for happy than angry faces in autistic participants. Drift diffusion modelling confirmed HSF advantage and showed a longer non-decision time (e.g., encoding) in autism. Despite LSF predictive impairments in autism was not corroborated, our analyses suggest low level processing specificities in autism.

The Role of Decision-Making in Psychological Wellbeing and Risky Behaviours in Autistic Adolescents Without ADHD: Longitudinal Evidence from the UK Millennium Cohort Study

This study examined the development of decision-making and its association with psychological wellbeing and risky behaviours in adolescents with and without autism. Participants included 270 autistic and 9,713 typically developing adolescents. In both samples, those with a diagnosis of attention-deficit/hyperactivity disorder (ADHD) were excluded. Data came from the Millennium Cohort Study, a nationally representative population-based birth cohort. Decision-making was assessed using the Cambridge Gambling Task at ages 11 and 14. Psychological wellbeing (happiness, self-esteem, depressive symptoms and self-harm) and risky/antisocial behaviours were self-reported at age 14. After adjusting for sex, cognitive ability, spatial working memory, socioeconomic status and pubertal status, autistic adolescents showed comparable quality of decision-making to that of their peers at both ages but also a more deliberative decision-making style as they aged. Only in autistic adolescents was this decision-making style associated with positive outcomes.

Understanding Speed-Accuracy Processing Dynamics in Aphasia Using Response Time Modeling

People with aphasia demonstrate language impairments evident in both performance accuracy and processing speed, but the direct relationship between accuracy and speed requires further consideration. This article describes two recent attempts to make quantitative progress in this domain using response time modeling: the diffusion model (Ratcliff, 1978) applied to two-choice tasks and a multinomial ex-Gaussian model applied to picture naming. The diffusion model may be used to characterize core linguistic processing efficiency and speed-accuracy tradeoffs independently, and research suggests that maladaptive speed-accuracy tradeoffs lead to performance impairments in at least some people with aphasia. The multinomial ex-Gaussian response time model of picture naming provides a simple and straightforward way to estimate the optimal response time cutoffs for individual people with aphasia (i.e., the cutoff where additional time is unlikely to lead to a correct response). While response time modeling applied to aphasia research is at an early stage of development, both the diffusion model and multinomial ex-Gaussian response time model of picture naming show promise and should be further developed in future work. This article also provides preliminary recommendations for clinicians regarding how to conceptualize, identify, and potentially address maladaptive speed-accuracy tradeoffs for people with aphasia.

Prior information use and response caution in perceptual decision-making: No evidence for a relationship with autistic-like traits

Interpreting the world around us requires integrating incoming sensory signals with prior information. Autistic individuals have been proposed to rely less on prior information and make more cautious responses than non-autistic individuals. Here, we investigated whether these purported features of autistic perception vary as a function of autistic-like traits in the general population. We used a diffusion model framework, whereby decisions are modelled as noisy evidence accumulation processes towards one of two bounds. Within this framework, prior information can bias the starting point of the evidence accumulation process. Our pre-registered hypotheses were that higher autistic-like traits would relate to reduced starting point bias caused by prior information and increased response caution (wider boundary separation). 222 participants discriminated the direction of coherent motion stimuli as quickly and accurately as possible. Stimuli were preceded with a neutral cue (square) or a directional cue (arrow). 80% of the directional cues validly predicted the upcoming motion direction. We modelled accuracy and response time data using a hierarchical Bayesian model in which starting point varied with cue condition. We found no evidence for our hypotheses, with starting point bias and response caution seemingly unrelated to Adult Autism Spectrum Quotient (AQ) scores. Alongside future research applying this paradigm to autistic individuals, our findings will help refine theories regarding the role of prior information and altered decision-making strategies in autistic perception. Our study also has implications for models of bias in perceptual decision-making, as the most plausible model was one that incorporated bias in both decision-making and sensory processing.

Global disruption in excitation-inhibition balance can cause localized network dysfunction and Schizophrenia-like context-integration deficits

Poor context integration, the process of incorporating both previous and current information in decision making, is a cognitive symptom of schizophrenia. The maintenance of the contextual information has been shown to be sensitive to changes in excitation-inhibition (EI) balance. Many regions of the brain are sensitive to EI imbalances, however, so it is unknown how systemic manipulations affect the specific regions that are important to context integration. We constructed a multi-structure, biophysically-realistic agent that could perform context-integration as is assessed by the dot pattern expectancy task. The agent included a perceptual network, a memory network, and a decision making system and was capable of successfully performing the dot pattern expectancy task. Systemic manipulation of the agent’s EI balance produced localized dysfunction of the memory structure, which resulted in schizophrenia-like deficits at context integration. When the agent’s pyramidal cells were less excitatory, the agent fixated upon the cue and initiated responding later than the default agent, which were like the deficits one would predict that individuals on the autistic spectrum would make. This modelling suggests that it may be possible to parse between different types of context integration deficits by adding distractors to context integration tasks and by closely examining a participant’s reaction times.

Schizophrenia is a debilitating mental health disorder and its underlying etiology is currently unknown. Neural imbalances in the neural excitation and inhibition of specific regions of the brain have been hypothesized to cause symptoms of schizophrenia. Most regions of the brain have specific excitation-inhibition balances that permit their functioning in the processing of information. How systemic changes in the excitation-inhibition balance cause specific deficits and dysfunction within neural circuits is unknown. A common cognitive deficit in schizophrenia is difficulty with context integration, which is the ability to successfully use previous and current information when making decisions. We assessed how this symptom could be caused by an imbalance in neural excitation and inhibition by simulating the effects of potential imbalances in a model agent. Global imbalances in the agent’s neural excitation and inhibition led to impairment of specific circuits. These dysfunctional circuits produced behavioral deficits that were like those observed in individuals with schizophrenia. These simulations suggested how specific neural circuits may be disrupted by global changes in excitation or inhibition, ways to improve the assessment of context integration, new approaches to analyzing behavior, and why it may be beneficial to assess context integration in autism spectrum disorder.

Shifting attention between modalities: Revisiting the modality-shift effect in autism

Selective attention to a sensory modality has been observed experimentally in studies of the modality-shift effect – a relative performance benefit for targets preceded by a target in the same modality, compared to a different modality. Differences in selective attention are commonly observed in autism and we investigated whether exogenous (automatic) shift costs between modalities are increased. Autistic adults and neurotypical controls made speeded discrimination responses to simple visual, tactile and auditory targets. Shift costs were observed for each target modality in participant response times and were largest for auditory targets, reflective of fast responses on auditory repeat trials. Critically, shift costs were similar between the groups. However, integrating speed and accuracy data using drift-diffusion modelling revealed that shift costs in drift rates (reflecting the quality of information extracted from the stimulus) were reduced for autistic participants compared with neurotypicals. It may be that, unlike neurotypicals, there is little difference between attention within and between sensory modalities for autistic people. This finding also highlights the benefit of combining reaction time and accuracy data using decision models to better characterise selective attention in autism.

Self-reported impulsivity does not predict response caution

The broad construct of impulsivity is one that spans both personality and cognitive ability. Despite a common overarching construct, previous research has found no relationship between self-report measures of impulsivity and people's ability to inhibit pre-potent responses. Here, we use evidence accumulation models of choice reaction time tasks to extract a measure of "response caution" (boundary separation) and examine whether this correlates with self-reported impulsivity as measured by the UPPS-P questionnaire. Response caution reflects whether an individual makes decisions based on more (favouring accuracy) or less (favouring speed) evidence. We reasoned that this strategic dimension of behaviour is conceptually closer to the tendencies that self-report impulsivity measures probe than what is traditional measured by inhibition tasks. In a meta-analysis of five datasets (total N = 296), encompassing 19 correlations per subscale, we observe no evidence that response caution correlates with self-reported impulsivity. Average correlations between response caution and UPPS-P subscales ranged from rho = -0.02 to -0.04. While the construct of response caution has demonstrated value in understanding individual differences in cognition, brain functioning and aging; the factors underlying what has been called "impulsive information processing" appear to be distinct from the concept of impulsivity derived from self-report.

Increased pain sensitivity and pain-related anxiety in individuals with autism

INTRODUCTION

Individuals with autism spectrum disorder (ASD) often exhibit differences in pain responsivity. This altered responsivity could be related to ASD-related social communication difficulties, sensory differences, or altered processing of pain stimuli. Previous neuroimaging work suggests altered pain evaluation could contribute to pain-related anxiety in ASD.

OBJECTIVES

We hypothesized that individuals with ASD would report increased pain sensitivity and endorse more pain-related anxiety, compared to typically developing controls.

METHODS

We recruited 43 adults (ASD, n = 24; typically developing, n = 19) for 3 heat pain tasks (applied to the calf). We measured heat pain thresholds using a method of limits approach, a pain-rating curve (7 temperatures between 40 and 48°C, 5 seconds, 5 trials each), and a sustained heat pain task with alternating low (42°C) and high (46°C) temperatures (21 seconds, 6 trials each). Individual differences in pain-related anxiety, fear of pain, situational pain catastrophizing, depressive symptoms, and autism-related social communication were assessed by self-report.

RESULTS

There were no group differences in pain thresholds. For suprathreshold tasks, mean pain ratings were higher in ASD across both the pain-rating curve and the sustained heat pain tasks, but responses in the ASD group were more varied. Pain anxiety (PASS-Total) and pain-related fear (FOP-III-Total) were higher in the ASD group and were positively associated with pain ratings.

CONCLUSIONS

Our results suggest that both sensory and cognitive experiences of pain are heightened and interact reciprocally in adults with ASD. Future studies are needed to evaluate the impact of pain-related anxiety on treatment-seeking and pain behaviors, given higher levels of pain-related anxiety in ASD.

Quantifying the benefits of using decision models with response time and accuracy data

Response time and accuracy are fundamental measures of behavioral science, but discerning participants' underlying abilities can be masked by speed-accuracy trade-offs (SATOs). SATOs are often inadequately addressed in experiment analyses which focus on a single variable or which involve a suboptimal analytic correction. Models of decision-making, such as the drift diffusion model (DDM), provide a principled account of the decision-making process, allowing the recovery of SATO-unconfounded decision parameters from observed behavioral variables. For plausible parameters of a typical between-groups experiment, we simulate experimental data, for both real and null group differences in participants' ability to discriminate stimuli (represented by differences in the drift rate parameter of the DDM used to generate the simulated data), for both systematic and null SATOs. We then use the DDM to fit the generated data. This allows the direct comparison of the specificity and sensitivity for testing of group differences of different measures (accuracy, reaction time, and the drift rate from the model fitting). Our purpose here is not to make a theoretical innovation in decision modeling, but to use established decision models to demonstrate and quantify the benefits of decision modeling for experimentalists. We show, in terms of reduction of required sample size, how decision modeling can allow dramatically more efficient data collection for set statistical power; we confirm and depict the non-linear speed-accuracy relation; and we show how accuracy can be a more sensitive measure than response time given decision parameters which reasonably reflect a typical experiment.

Identifying Feigned Cognitive Impairment: Investigating the Utility of Diffusion Model Analyses

Forced-choice performance validity tests are routinely used for the detection of feigned cognitive impairment. The drift diffusion model deconstructs performance into distinct cognitive processes using accuracy and response time measures. It thereby offers a unique approach for gaining insight into examinees' speed-accuracy trade-offs and the cognitive processes that underlie their performance. The current study is the first to perform such analyses using a well-established forced-choice performance validity test. To achieve this aim, archival data of healthy participants, either simulating cognitive impairment in the Word Memory Test or performing it to the best of their ability, were analyzed using the EZ-diffusion model (N = 198). The groups differed in the three model parameters, with drift rate emerging as the best predictor of group membership. These findings provide initial evidence for the usefulness of the drift diffusion model in clarifying the cognitive processes underlying feigned cognitive impairment and encourage further research.

Neural correlates of cognitive variability in childhood autism and relation to heterogeneity in decision-making dynamics

Heterogeneity in cognitive and academic abilities is a prominent feature of autism spectrum disorder (ASD), yet little is known about its underlying causes. Here we combine functional brain imaging during numerical problem-solving with hierarchical drift-diffusion models of behavior and standardized measures of numerical abilities to investigate neural mechanisms underlying cognitive variability in children with ASD, and their IQ-matched Typically Developing (TD) peers. Although the two groups showed similar levels of brain activation, the relation to individual abilities differed markedly in ventral temporal-occipital, parietal and prefrontal regions important for numerical cognition: children with ASD showed a positive correlation between functional brain activation and numerical abilities, whereas TD children showed the opposite pattern. Despite similar accuracy and response times, decision thresholds were significantly higher in the ASD group, suggesting greater evidence required for problem-solving. Critically, the relationship between individual abilities and engagement of prefrontal control systems anchored in the anterior insula was differentially moderated by decision threshold in subgroups of children with ASD. Our findings uncover novel cognitive and neural sources of variability in academically-relevant cognitive skills in ASD and suggest that multilevel measures and latent decision-making dynamics can aid in characterization of cognitive variability and heterogeneity in neurodevelopmental disorders.

Using drift diffusion modeling to understand inattentive behavior in preterm and term-born children

Objective: Children born very preterm are at increased risk of inattention, but it remains unclear whether the underlying processes are the same as in their term-born peers. Drift diffusion modeling (DDM) may better characterize the cognitive processes underlying inattention than standard reaction time (RT) measures. This study used DDM to compare the processes related to inattentive behavior in preterm and term-born children. Method: Performance on a cued continuous performance task was compared between 33 children born very preterm (VP; ≤32 weeks’ gestation) and 32 term-born peers (≥37 weeks’ gestation), aged 8–11 years. Both groups included children with a wide spectrum of parent-rated inattention (above average attention to severe inattention). Performance was defined using standard measures (RT, RT variability and accuracy) and modeled using a DDM. A hierarchical regression assessed the extent to which standard or DDM measures explained variance in parent-rated inattention and whether these relationships differed between VP and term-born children. Results: There were no group differences in performance on standard or DDM measures of task performance. Parent-rated inattention correlated significantly with hit rate, RT variability, and drift rate (a DDM estimate of processing efficiency) in one or both groups. Regression analysis revealed that drift rate was the best predictor of parent-rated inattention. This relationship did not differ significantly between groups. Conclusions: Findings suggest that less efficient information processing is a common mechanism underlying inattention in both VP and term-born children. This study demonstrates the benefits of using DDM to better characterize atypical cognitive processing in clinical samples.

Less efficient information processing during a sustained attention task explained individual differences in inattentive behavior. This was true both in 8- to 11-year-olds born very preterm and their term-born peers. Drift diffusion modeling provides a way to help us better characterize the processes that underlie task performance. This is valuable for understanding processing differences that affect clinical groups.

Slow and steady? Strategic adjustments in response caution are moderately reliable and correlate across tasks

Speed-accuracy trade-offs are often considered a confound in speeded choice tasks, but individual differences in strategy have been linked to personality and brain structure. We ask whether strategic adjustments in response caution are reliable, and whether they correlate across tasks and with impulsivity traits. In Study 1, participants performed Eriksen flanker and Stroop tasks in two sessions four weeks apart. We manipulated response caution by emphasising speed or accuracy. We fit the diffusion model for conflict tasks and correlated the change in boundary (accuracy - speed) across session and task. We observed moderate test-retest reliability, and medium to large correlations across tasks. We replicated this between-task correlation in Study 2 using flanker and perceptual decision tasks. We found no consistent correlations with impulsivity. Though moderate reliability poses a challenge for researchers interested in stable traits, consistent correlation between tasks indicates there are meaningful individual differences in the speed-accuracy trade-off.

Explaining hyper-sensitivity and hypo-responsivity in autism with a common predictive coding-based mechanism

Ward's signal detection theory-based framework elucidates some aspects of interindividual differences in sensitivity, but, we argue, obscures others. Specifically, it disregards the important challenge of inferring the meaning of sensory inputs. Within Bayesian predictive coding accounts, the meaning is given by inferences to more deeply hidden causes of sensory inputs and is generally the basis for initiating context-appropriate (e.g., social) behavior. As such, when inference of hierarchical causes is hampered, as accounts of autism based on deficient precision estimation imply, a form of hyporesponsivity can emerge (together with the hypersensitivity already highlighted by Ward).

Error monitoring in decision-making and timing is disrupted in autism spectrum disorder

Individuals with autism spectrum disorder (ASD) have difficulties in social interactions. The cognitive domains that support these interactions include perceptual decision-making, timing, and error-monitoring, which enable one to appropriately understand and react to the other individual in communicative settings. This study constitutes a comprehensive exploration of decision-making and interval timing in ASD as well as the first investigation of error-monitoring abilities of individuals with ASD regarding their performance in the corresponding domains. We found that children with ASD fared similar to typically developing (TD) children in their first-order task performance in two-alternative forced choice perceptual decision-making and temporal reproduction tasks as well as the secondary tasks (signal detection and free finger tapping tasks). Yet, they had a deficit in error-monitoring in both tasks where their accuracy did not predict their confidence ratings, which was the case for the TD group. The difference between ASD and TD groups was limited to error-monitoring performance. This study attests to a circumscribed impairment in error-monitoring in individuals with ASD, which may partially underlie their social interaction problems. This difficulty in cognitively evaluating one's own performance may also relate to theory of mind deficits reported for individuals with ASD, where they struggle in understanding the mental states and intentions of others. This novel finding holds the potential to inform effective interventions for individuals with ASD that can target this error-monitoring ability to have broad-ranging effects in multiple domains involved in communication and social interaction. Autism Res 2019, 12: 239-248 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Decision-making, timing, and error-monitoring are three of many abilities that underlie smooth social interactions. To date, these domains have been only investigated separately, but given their interactive role in social interactions that are impaired in ASD, we conducted the first study to investigate them together. Children with ASD were as successful as typically developing children in their task performances, but unlike them, were unaware of their errors in both decision-making and timing tasks. This deficit that is limited to error-monitoring can contribute to unraveling the unique cognitive signature of ASD and to formulating interventions with positive implications in multiple domains.

Overlapping and Distinct Cognitive Impairments in Attention-Deficit/Hyperactivity and Autism Spectrum Disorder without Intellectual Disability

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are commonly comorbid, share genetic liability, and often exhibit overlapping cognitive impairments. Clarification of shared and distinct cognitive effects while considering comorbid symptoms across disorders has been lacking. In the current study, children ages 7-15 years assigned to three diagnostic groups:ADHD (n = 509), ASD (n = 97), and controls (n = 301) completed measures spanning the cognitive domains of attention/arousal, working memory, set-shifting, inhibition, and response variability. Specific processes contributing to response variability were examined using a drift diffusion model, which separately quantified drift rate (i.e., efficiency of information processing), boundary separation (i.e., speed-accuracy trade-offs), and non-decision time. Children with ADHD and ASD were impaired on attention/arousal, processing speed, working memory, and response inhibition, but did not differ from controls on measures of delayed reward discounting, set-shifting, or interference control. Overall, impairments in the ASD group were not attributable to ADHD symptoms using either continuous symptom measures or latent categorical grouping approaches. Similarly, impairments in the ADHD group were not attributable to ASD symptoms. When specific RT parameters were considered, children with ADHD and ASD shared impairments in drift rate. However, children with ASD were uniquely characterized by a wider boundary separation. Findings suggest a combination of overlapping and unique patterns of cognitive impairment for children with ASD as compared to those with ADHD, particularly when the processes underlying reaction time measures are considered separately.

Autistic Traits in the Neurotypical Population do not Predict Increased Response Conservativeness in Perceptual Decision Making

Recent research has shown that adults and children with autism spectrum disorders have a more conservative decision criterion in perceptual decision making compared to neurotypical individuals, meaning that autistic participants prioritise accuracy over speed of a decision. Here, we test whether autistic traits in the neurotypical population correlate with increased response conservativeness. We employed three different tasks; for two tasks we recruited participants from China ( N = 39) and for one task from the United Kingdom ( N = 37). Our results show that autistic traits in the neurotypical population do not predict variation in response criterion. We also failed to replicate previous work showing a relationship between autistic traits and sensitivity to coherent motion and static orientation. Following the argument proposed by Gregory and Plaisted-Grant, we discuss why perceptual differences between autistic and neurotypical participants do not necessarily predict perceptual differences between neurotypical participants with high and low autistic traits.

Lateral inhibition in the autism spectrum: An SSVEP study of visual cortical lateral interactions

Circuit level brain dysfunction has been suggested as a common mechanism through which diverse genetic risk factors and neurobiological sequelae lead to the core features of autism spectrum disorder (Geschwind 2009; Port et al. 2014). An important mediator of circuit level brain activity is lateral inhibition, and a number of authors have suggested that lateral inhibition may be atypical in ASD. However, evidence regarding putative atypical lateral connections in ASD is mixed. Here we employed a steady state visual evoked potential (SSVEP) paradigm to further investigate lateral connections within a group of high functioning adults with ASD. At a group level, we found no evidence of altered lateral interactions in ASD. Exploratory analyses reveal that greater ASD symptom severity (increased ADOS score) is associated with increased short range lateral inhibition. These results suggest that lateral interactions are not altered in ASD at a group-level, but that subtle alterations in such neurobiological processes may underlie the heterogeneity seen in the autism spectrum in terms of sensory perception and behavioral phenotype.