Central tendency effects in time interval reproduction in autism

Abstract

Central tendency, the tendency of judgements of quantities (lengths, durations etc.) to gravitate towards their mean, is one of the most robust perceptual effects. A Bayesian account has recently suggested that central tendency reflects the integration of noisy sensory estimates with prior knowledge representations of a mean stimulus, serving to improve performance. The process is flexible, so prior knowledge is weighted more heavily when sensory estimates are imprecise, requiring more integration to reduce noise. In this study we measure central tendency in autism to evaluate a recent theoretical hypothesis suggesting that autistic perception relies less on prior knowledge representations than typical perception. If true, autistic children should show reduced central tendency than theoretically predicted from their temporal resolution. We tested autistic and age- and ability-matched typical children in two child-friendly tasks: (1) a time interval reproduction task, measuring central tendency in the temporal domain; and (2) a time discrimination task, assessing temporal resolution. Central tendency reduced with age in typical development, while temporal resolution improved. Autistic children performed far worse in temporal discrimination than the matched controls. Computational simulations suggested that central tendency was much less in autistic children than predicted by theoretical modelling, given their poor temporal resolution.

A Perceptual Inference Mechanism for Hallucinations Linked to Striatal Dopamine

“…We illustrate with simulations how a simple Bayesian model produces an uncertainty-dependent assimilation bias in Figure 1D, similar to prior work [83, 85, 93]. The model assumes that subjects estimate the true duration of the target tone ( μ target ) as if it were drawn from a noisy, Gaussian distribution, from which context tone durations are also drawn.…”

Aberrant Sensory Encoding in Patients with Autism

“…In conclusion, recent theories within computational psychiatry have proposed that a range of psychopathological disorders, most notably Autism (Pellicano & Burr, 2012;Van der Cruys et al, 2014;Lawson et al, 2014) but also Schizophrenia Corlett et al, 2009;Adams et al, 2013), are underpinned by deficits in performing Bayesian inference: the ability to correctly integrate sensory information with prior knowledge. These psychiatric-focused Bayesian theories, however, have so far largely ignored the possibility that the encoding of sensory information itself could be affected (but see Karaminis et al, 2016;Karvelis et al, 2018). They generally assumed that the generation of likelihood functions (encoding) and its combination with a prior (decoding) are independent processes.…”

“…Recent theories attempting to provide a normative account for the complex phenotype of Autism Spectrum Disorder (ASD) have used the language of statistical inference, proposing that prior knowledge about the world is under-emphasized relative to incoming sensory information in patients with ASD. The primary source of this imbalance is debated: some authors argue for attenuated priors (Karaminis et al, 2016;Pellicano and Burr, 2012a;2012b;Powell et al, 2016), while others argue for aberrant sensory precision or prediction error (Karvelis et al, 2018;Lawson et al, 2014;Palmer et al, 2017;Brock, 2012;Van de Cruys et al, 2013). In common, however, these studies are disproportionally emphasizing the interpretation of incoming sensory information (i.e., decoding) while ignoring the possibility that deficits in the neural representation of sensory information (i.e., encoding) may also be responsible for the observed differences in perceptual behavior between ASD and healthy populations.…”

Visual landmarks calibrate auditory space across eye movements

“…This indicates that the range of auditory responses across different pre-saccadic locations was compressed and exhibited a central tendency (i.e. a bias towards the average stimulus location; (Karaminis et al, 2016;Watson, 1957)).…”