Implicit Versus Explicit Metacognition in ASD

Poster Presentation
Thursday, May 10, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
D. M. Williams1, T. Nicholson2, C. Grainger3, P. Carruthers4 and S. E. Lind5, (1)University of Kent, Canterbury, United Kingdom, (2)University of Kent, Canterbury, England, United Kingdom, (3)University of Stirling, Stirling, United Kingdom, (4)University of Maryland, College Park, MD, (5)Psychology, City, University of London, London, United Kingdom
Background: The few existing studies of metacognitive monitoring (awareness of one’s own mental states/cognition) in ASD have employed tests that require participants to make explicit judgements about the state of their own knowledge. The closer the correspondence between judgements of one’s knowledge and actual (objectively-measured) knowledge, the more accurate metacognitive monitoring is. Findings using such explicit tasks have been mixed. In the current investigation, we employed not only a standard test of explicit metacognitive monitoring, but also a paradigm adapted from one used in comparative psychology to assess metacognitive monitoring non-verbally/implicitly.

Objectives: The aim of the present study was to investigate implicit and explicit metacognition, and their relations to mentalizing ability, in ASD.

Methods: 21 participants with ASD and 21 age- and IQ-matched comparison participants completed an “uncertainty monitoring” paradigm based on that used among non-human primates. This involved a visual discrimination task (e.g., judging the most pixelated of two squares). On each trial (see Figure 1), two squares and a red (“opt out”) arrow appeared. If participants chose the most pixilated square, they gained money, whereas if they chose the least pixilated square they lost money. Choosing the arrow moved on to the next trial without penalty or loss. Adaptive performance would be indicated by use of the opt-out arrow on difficult trials that the participant would likely have got incorrect.

In a second session, participants completed the same monitoring task, but requiring different visual discriminations and without the presence of the opt-out arrow (see Figure 2). This time, after each discrimination trial, participants were asked to choose between the options “confident” or “not confident”. Accurate metacognitive monitoring was indicated by a greater tendency to choose “confident” on successful visual discrimination trials than on unsuccessful trials and, vice versa, to choose “not confident” more on unsuccessful than successful trials.

Results: In the implicit task, discrimination difficulty was significantly higher on trials that were opted out of than trials that were opted into, reflecting adaptive performance. There was no difference between the groups in this respect, p = .33, d = 0.31. However, in the explicit task, the judgements of confidence (JOC) were significantly less accurate (i.e., less in line with actual performance) among ASD than comparison participants, reflecting diminished explicit metacognitive monitoring, p = .04, d = 0.66. Importantly, mentalizing ability (measured using the Animations and Reading the Mind in the Eyes tasks) accounted for a significant 14% of the variance in explicit task performance, but only a non-significant 2% of the variance in implicit task performance.

Conclusions: These results show an impairment in explicit metacognition that is related to established mentalizing impairments in ASD, which supports the “one-system” theory of the relation between mentalizing and metacognition (e.g., Carruthers, 2009). However, they also suggest that decision-making can be adaptive in people with ASD. Nonetheless, the extent to which such decision-making is truly metacognitive/metarepresentational will be discussed.