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

Autistic traits foster effective curiosity-driven exploration

Curiosity-driven exploration involves actively engaging with the environment to learn from it. Here, we hypothesize that the cognitive mechanisms underlying exploratory behavior may differ across individuals depending on personal characteristics such as autistic traits. In turn, this variability might influence successful exploration. To investigate this, we collected self- and other-reports of autistic traits from university students, and tested them in an exploration task in which participants could learn the hiding patterns of multiple characters. Participants' prediction errors and learning progress (i.e., the decrease in prediction error) on the task were tracked with a hierarchical delta-rule model. Crucially, participants could freely decide when to disengage from a character and what to explore next. We examined whether autistic traits modulated the relation of prediction errors and learning progress with exploration. We found that participants with lower scores on other-reports of insistence-on-sameness and general autistic traits were less persistent, primarily relying on learning progress during the initial stages of exploration. Conversely, participants with higher scores were more persistent and relied on learning progress in later phases of exploration, resulting in better performance in the task. This research advances our understanding of the interplay between autistic traits and exploration drives, emphasizing the importance of individual traits in learning processes and highlighting the need for personalized learning approaches.

Thinking, fast and slow on the autism spectrum

What is already known about the topicDaniel Kahneman wrote a highly influential book titled 'thinking, fast and slow'. He proposes that people usually think in a rapid, automatic, intuitive style. When people realise their intuitive thinking may be wrong, a slower, effortful, deliberative style of thinking takes over. It has recently been proposed that thinking in autistic individuals can be characterised as usually thinking in the deliberative style (rather than the intuitive style that non-autistic people usually think in).What this paper addsAs intuitive thinking is fast and deliberative thinking is slow, this research manipulated the time available to complete a series of reasoning questions. These questions have been developed to have intuitive answers (which are incorrect) and deliberative answers (which are correct). For the first time, a fast time manipulation (you must answer quickly) and slow (you must think about your answer before responding) was undertaken with autistic individuals. Autistic participants did produce more deliberative answers than the non-autistic participants. However, both groups produced comparably more intuitive answers and less deliberative answers in the fast condition. This shows that while autistic people tend not to use their intuition, autistic people can be encouraged to use their intuition.Implications for practice, research or policyUsing rapid intuition can be useful in fast-changing contexts, such as some social situations. Future research can explore how to support autistic individuals to use their intuition when the need arises. In addition, the propensity for deliberation resulting in unbiased, correct responses reflects a strengths-based account of autism. This requires more mental effort and is less susceptible to bias and errors. This is called 'Dual Process Theory'.

No increased circular inference in adults with high levels of autistic traits or autism

Autism spectrum disorders have been proposed to arise from impairments in the probabilistic integration of prior knowledge with sensory inputs. Circular inference is one such possible impairment, in which excitation-to-inhibition imbalances in the cerebral cortex cause the reverberation and amplification of prior beliefs and sensory information. Recent empirical work has associated circular inference with the clinical dimensions of schizophrenia. Inhibition impairments have also been observed in autism, suggesting that signal reverberation might be present in that condition as well. In this study, we collected data from 21 participants with self-reported diagnoses of autism spectrum disorders and 155 participants with a broad range of autistic traits in an online probabilistic decision-making task (the fisher task). We used previously established Bayesian models to investigate possible associations between autistic traits or autism and circular inference. There was no correlation between prior or likelihood reverberation and autistic traits across the whole sample. Similarly, no differences in any of the circular inference model parameters were found between autistic participants and those with no diagnosis. Furthermore, participants incorporated information from both priors and likelihoods in their decisions, with no relationship between their weights and psychiatric traits, contrary to what common theories for both autism and schizophrenia would suggest. These findings suggest that there is no increased signal reverberation in autism, despite the known presence of excitation-to-inhibition imbalances. They can be used to further contrast and refine the Bayesian theories of schizophrenia and autism, revealing a divergence in the computational mechanisms underlying the two conditions.

The effect of autism on information sampling during decision-making: An eye-tracking study

Recent research has highlighted a tendency for more rational and deliberative decision-making in individuals with autism. We tested this hypothesis by using eye-tracking to investigate the information processing strategies that underpin multi-attribute choice in a sample of adults diagnosed with autism spectrum condition. We found that, as the number of attributes defining each option increased, autistic decision-makers were speedier, examined less of the available information, and spent a greater proportion of their time examining the option they eventually chose. Rather than indicating a more deliberative style, our results are consistent with a tendency for individuals with autism to narrow down the decision-space more quickly than does the neurotypical population.