Reduced Context Updating but Intact Visual Priors in Autism
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Abstract
A general consensus persists that sensory-perceptual differences in autism, such as hypersensitivities to light or sound, result from an overreliance on new (rather than prior) sensory observations. However, conflicting Bayesian accounts of autism remain unresolved as to whether such alterations are caused by more precise sensory observations (precise likelihood model) or by forming a less precise model of the sensory context (hypo-priors model). We used a decision-under-uncertainty paradigm that manipulated uncertainty in both likelihoods and priors. Contrary to model predictions we found no differences in reliance on likelihood in autistic group (AS) compared to neurotypicals (NT) and found no differences in subjective prior variance between groups. However, we found reduced context adjustment in the AS group compared to NT. Further, the AS group showed heightened variability in their relative weighting of sensory information (vs. prior) on a trial-by-trial basis. When participants were aligned on a continuum of autistic traits, we found no associations with likelihood reliance or prior variance but found an increase in likelihood precision with autistic traits. These findings together provide empirical evidence for intact priors, precise likelihood, reduced context updating and heightened variability during sensory learning in autism.
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A recent study by Shi et al. investigated prior updating in ASD using the central tendency effect in combination with Kalman, finding an initial underweighting of priors in autistic adults that normalised by the end of the task.
“For example, a recent study by Shi et al. [5] investigated prior updating in ASD using the central tendency effect in combination with Kalman. They found an initial underweighting of priors in autistic adults, resonating with some previous findings indicating atypical priors [13, 56], which normalised by the end of the task, resonating with contrasting previous findings of intact priors in ASD [57”
From Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework (2026) · cites this paper as [57]
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Cites
An inventory for measuring depression
BECK, A. T. (1961) · Archives of General Psychiatry · doi:10.1001/archpsyc.1961.01710120031004 · Cited by 38,032 · see citing works
Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4 · Cited by 33,612 · see citing works
An inventory for measuring clinical anxiety: Psychometric properties.
Beck, A. T., Epstein, N., Brown, G., & Steer, R. A. (1988) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.56.6.893 · Cited by 14,407 · see citing works
Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4_9 · Cited by 12,675 · see citing works
Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1005653411471 · Cited by 6,450 · see citing works
Bayesian integration in sensorimotor learning
Körding, K. P., & Wolpert, D. M. (2004) · Nature · doi:10.1038/nature02169 · Cited by 2,004 · see citing works
Enhanced Perceptual Functioning in Autism: An Update, and Eight Principles of Autistic Perception
Mottron, L., Dawson, M., Soulières, I., Hubert, B., & Burack, J. (2006) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-005-0040-7 · Cited by 1,957 · see citing works
Journal of Autism and Developmental Disorders
(2013) · Journal of Autism and Developmental Disorders · doi:10.1007/10803.1573-3432 · Cited by 1,358 · see citing works
The Autism Diagnostic Observation Schedule: Revised Algorithms for Improved Diagnostic Validity
Gotham, K., Risi, S., Pickles, A., & Lord, C. (2007) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-006-0280-1 · Cited by 1,161 · see citing works
When the world becomes ‘too real’: a Bayesian explanation of autistic perception
Pellicano, E., & Burr, D. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.08.009 · Cited by 1,156 · see citing works
Precise minds in uncertain worlds: Predictive coding in autism.
Van de Cruys, S., Evers, K., Van der Hallen, R., Van Eylen, L., Boets, B., de-Wit, L., & Wagemans, J. (2014) · Psychological Review · doi:10.1037/a0037665 · Cited by 885 · see citing works
Talent in autism: hyper-systemizing, hyper-attention to detail and sensory hypersensitivity
Baron-Cohen, S., Ashwin, E., Ashwin, C., Tavassoli, T., & Chakrabarti, B. (2009) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2008.0337 · Cited by 669 · see citing works
An aberrant precision account of autism
Lawson, R. P., Rees, G., & Friston, K. J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00302 · Cited by 641 · see citing works
Sensory processing in adults with autism spectrum disorders.
Crane, L., Goddard, L., & Pring, L. (2009) · Autism · doi:10.1177/1362361309103794 · Cited by 602 · see citing works
Hus, V., & Lord, C. (2014) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-014-2080-3 · Cited by 547 · see citing works
Confidence and certainty: Distinct probabilistic quantities for different goals
Pouget, A., Drugowitsch, J., & Kepecs, A. (2016) · Nature Neuroscience · doi:10.1038/nn.4240 · Cited by 528 · see citing works
Enhanced visual search for a conjunctive target in autism: a research note
Plaisted, K., O'Riordan, M., & Baron-Cohen, S. (1998) · Journal of Child Psychology and Psychiatry · doi:10.1017/s0021963098002613 · Cited by 405 · see citing works
Wigham, S., Rodgers, J., South, M., McConachie, H., & Freeston, M. (2015) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-014-2248-x · Cited by 373 · see citing works
Why is visual search superior in autism spectrum disorder?
Joseph, R. M., Keehn, B., Connolly, C., Wolfe, J. M., & Horowitz, T. S. (2009) · Developmental Science · doi:10.1111/j.1467-7687.2009.00855.x · Cited by 313 · see citing works
Mottron, L., Peretz, I., & Ménard, É. (2000) · Journal of Child Psychology and Psychiatry · doi:10.1111/1469-7610.00693 · Cited by 292 · see citing works
Sensory over-responsivity in adults with autism spectrum conditions
Tavassoli, T., Miller, L. J., Schoen, S. A., Nielsen, D. M., & Baron-Cohen, S. (2014) · Autism · doi:10.1177/1362361313477246 · Cited by 291 · see citing works
Lidstone, J., Uljarević, M., Sullivan, J., Rodgers, J., McConachie, H., Freeston, M., Le Couteur, A., Prior, M., & Leekam, S. (2014) · Research in Autism Spectrum Disorders · doi:10.1016/j.rasd.2013.10.001 · Cited by 264 · see citing works
Tavassoli, T., Hoekstra, R. A., & Baron-Cohen, S. (2014) · Molecular Autism · doi:10.1186/2040-2392-5-29 · Cited by 251 · see citing works
Alternative Bayesian accounts of autistic perception: Comment on Pellicano and Burr
Brock, J. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.10.005 · Cited by 173 · see citing works
Differential Representations of Prior and Likelihood Uncertainty in the Human Brain
Vilares, I., Howard, J. D., Fernandes, H. L., Gottfried, J. A., & Kording, K. P. (2012) · Current Biology · doi:10.1016/j.cub.2012.07.010 · Cited by 165 · see citing works
Self-citationRelating inter-individual differences in metacognitive performance on different perceptual tasks
Song, C., Kanai, R., Fleming, S. M., Weil, R. S., Schwarzkopf, D. S., & Rees, G. (2011) · Consciousness and Cognition · doi:10.1016/j.concog.2010.12.011 · Cited by 158 · see citing works
Sensory Processing in Children with Autism Spectrum Disorders and Impact on Functioning
Suarez, M. A. (2012) · Pediatric Clinics of North America · doi:10.1016/j.pcl.2011.10.012 · Cited by 152 · see citing works
Mamassian, P. (2016) · Annual Review of Vision Science · doi:10.1146/annurev-vision-111815-114630 · Cited by 139 · see citing works
Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice?
Haker, H., Schneebeli, M., & Stephan, K. E. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00107 · Cited by 130 · see citing works
Comparing Bayesian and non-Bayesian accounts of human confidence reports
Adler, W. T., & Ma, W. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006572 · Cited by 118 · see citing works
Central tendency effects in time interval reproduction in autism
Karaminis, T., Cicchini, G. M., Neil, L., Cappagli, G., Aagten-Murphy, D., Burr, D., & Pellicano, E. (2016) · Scientific Reports · doi:10.1038/srep28570 · Cited by 112 · see citing works
Karvelis, P., Seitz, A. R., Lawrie, S. M., & Seriès, P. (2018) · eLife · doi:10.7554/elife.34115 · Cited by 112 · see citing works
Abu-Akel, A., Allison, C., Baron-Cohen, S., & Heinke, D. (2019) · Molecular Autism · doi:10.1186/s13229-019-0275-3 · Cited by 109 · see citing works
Chambon, V., Farrer, C., Pacherie, E., Jacquet, P. O., Leboyer, M., & Zalla, T. (2017) · Cognition · doi:10.1016/j.cognition.2016.12.005 · Cited by 95 · see citing works
Tauber, S., Navarro, D., Perfors, A., & Steyvers, M. (2017) · Psychological Review · doi:10.1037/rev0000052 · Cited by 88 · see citing works
Black, K. R., Stevenson, R. A., Segers, M., Ncube, B., Sun, S. Z., Philipp-Muller, A. Z., Bebko, J. M., Barense, M. D., & Ferber, S. (2017) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-017-3161-x · Cited by 86 · see citing works
Li, H.-H., & Ma, W. J. (2020) · Nature Communications · doi:10.1038/s41467-020-15581-6 · Cited by 81 · see citing works
Kim, H., Keifer, C. M., Rodriguez-Seijas, C. A., Eaton, N. R., Lerner, M. D., & Gadow, K. D. (2018) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2018.09.431 · Cited by 79 · see citing works
Perceptual inference and autistic traits
Skewes, J. C., Jegindø, E.-M., & Gebauer, L. (2015) · Autism · doi:10.1177/1362361313519872 · Cited by 71 · see citing works
Contextual priors do not modulate action prediction in children with autism
Amoruso, L., Narzisi, A., Pinzino, M., Finisguerra, A., Billeci, L., Calderoni, S., Fabbro, F., Muratori, F., Volzone, A., & Urgesi, C. (2019) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2019.1319 · Cited by 55 · see citing works
Intact priors for gaze direction in adults with high-functioning autism spectrum conditions
Pell, P. J., Mareschal, I., Calder, A. J., Hagen, E. V. D., Clifford, C. W. G., Baron‐Cohen, S., & Ewbank, M. (2016) · Molecular Autism · doi:10.1186/s13229-016-0085-9 · Cited by 48 · see citing works
The light-from-above prior is intact in autistic children
Croydon, A., Karaminis, T., Neil, L., Burr, D. C., & Pellicano, E. (2017) · Journal of Experimental Child Psychology · doi:10.1016/j.jecp.2017.04.005 · Cited by 43 · see citing works
Increased variability but intact integration during visual navigation in Autism Spectrum Disorder
Noel, J., Lakshminarasimhan, K. J., Park, H., & Angelaki, D. E. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2000216117 · Cited by 41 · see citing works
Bayesian Models of Brain and Behaviour
Penny, W. D. (2012) · ISRN Biomathematics · doi:10.5402/2012/785791 · Cited by 35 · see citing works
Dopaminergic medication increases reliance on current information in Parkinson’s disease
Vilares, I., & Kording, K. P. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0129 · Cited by 33 · see citing works
Self-citationThe role of priors in Bayesian models of perception
Teufel, C., Subramaniam, N., & Fletcher, P. C. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00025 · Cited by 26 · see citing works
Mottron, L. (2019) · Cognitive Neuroscience · doi:10.1080/17588928.2019.1596073 · Cited by 13 · see citing works
Karvelis, P., Seitz, A. R., Lawrie, S. M., et al. (2018) · doi:10.7554/elife.34115.032 · Cited by 3 · see citing works
Mottron, L. (2014) · Autism · doi:10.1177/1362361314558280 · Cited by 2 · see citing works
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Predicting emotional valence in autism: a preregistered study in the Bayesian Brain framework
Plank, I. S., Pior, A., Yurova, A., Nowak, J., Shi, Z., & Falter-Wagner, C. M. (2026) · Molecular Autism · doi:10.1186/s13229-026-00730-3 · Cited by 2 · see citing works
“They found an initial underweighting of priors in autistic adults, resonating with some previous findings indicating atypical priors [13, 56], which normalised by the end of the task, resonating with contrasting previous findings of intact priors in ASD [57].”
- Authors
- Randeniya, R., Vilares, I., Mattingley, J. B., & Garrido, M. I.
- Affiliations
- The University of Queensland (AU)
- University of Minnesota (US)
- Canadian Institute for Advanced Research (CA)
- The University of Melbourne (AU)
- Corresponding author
- Randeniya, R.
- Venue
- Computational Psychiatry
- Publisher
- Ubiquity Press, Ltd.
- Published
- 2021-12-29
- Volume
- 5
- Issue
- 1
- Pages
- 140
- ISSN
- 2379-6227 (ISSN-L)
- PMC
- PMC11104295
- OpenAlex
- W4226266233
- Cited by
- 17
- References
- 49
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 6 · 2023: 3 · 2022: 2
- FWCI
- 1.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Computational Psychiatry (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- University of Queensland (2016000071)
- Centre of Excellence for Integrative Brain Function, Australian Research Council (CE140100007)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- autism spectrum disorder, Bayesian models of perception, prior variance, context updating, sensory learning, decision making under uncertainty, autistic traits, sensory hypersensitivity, perceptual variability
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