Fig. 5
From: Suboptimal but intact integration of Bayesian components during perceptual decision-making in autism
Sensitivity, decision boundary, and optimal observer analyses for Experiment 2, sensory uncertainty manipulation. (a) Sensory uncertainty was evaluated by fitting the data with an SDT-style model adapted to the embedded category task. The fitted standard deviation, s, provided an estimate of sensory uncertainty. A higher value indicates more sensory uncertainty compared to a lower value. (b) Category boundaries k were estimated from the same model and assumed to be symmetrical about zero degrees; the positive value is shown. (c, d) Probability of the category distributions for each level of contrast. The solid lines represent the precision of the distribution, with the sensory uncertainty (s) as standard deviation of the category representations. The dashed lines represent the averaged decision boundaries (k) for each level of contrast (e) Deviation from optimality cerror as a function of contrast. Participants showed a larger deviation from the optimal decision boundaries as contrast decreased. Data points show means across participants and error bars represent ± SE. The sample size was 27 autistic and 40 non-autistic participants in (a-d), and 27 autistic and 38 non-autistic participants in (e)