High spatial frequency filtered primes hastens happy faces categorization in autistic adults
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Abstract
Coarse information of a visual stimulus is conveyed by Low Spatial Frequencies (LSF) and is thought to be rapidly extracted to generate predictions. This may guide fast recognition with the subsequent integration of fine information, conveyed by High Spatial Frequencies (HSF). In autism, emotional face recognition is challenging, and might be related to alterations in LSF predictive processes. We analyzed the data of 27 autistic and 34 non autistic (NA) adults on an emotional Stroop task (i.e., emotional face with congruent or incongruent emotional word) with spatially filtered primes (HSF vs.LSF). We hypothesized that LSF primes would generate predictions leading to faster categorization of the target face compared to HSF primes, in the NA group but not in autism. Surprisingly, HSF primes led to faster categorization than LSF primes in both groups. Moreover, the advantage of HSF vs.LSF primes was stronger for angry than happy faces in NA, but was stronger for happy than angry faces in autistic participants. Drift diffusion modelling confirmed HSF advantage and showed a longer non-decision time (e.g., encoding) in autism. Despite LSF predictive impairments in autism was not corroborated, our analyses suggest low level processing specificities in autism.
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Females outperformed males on interpersonal prediction tasks in autism spectrum disorder.
“Females outperformed males on interpersonal prediction tasks (Lacroix et al., 2021).”
From Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review. (2025) · cites this paper as Lacroix et al., 2021
The paper’s Sex differences section (4.4; page unavailable) says that although sex was considered, the best-performing model did not include it. Its task was emotional-face categorization, not an interpersonal prediction task, and it does not report autistic females outperforming males on that task. (LLM, conf=0.84)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredIndividuals with autism spectrum disorder show impaired non-social predictive abilities characterized by reduced neural activity in several areas, including those involved in decision-making, working memory, and sensory perception; this is manifested behaviorally as impaired eye gaze and slower reaction time.
“They show impaired non-social predictive abilities characterized by reduced neural activity in several areas, including those involved in decisionmaking, working memory, and sensory perception; this is manifested behaviorally as impaired eye gaze and slower reaction time (Greene et al., 2019; Lacroix et al., 2021).”
From Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review. (2025) · cites this paper as Lacroix et al., 2021
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Flagged first, then by citations
Research works printed but not linked: 1
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Cited by
Sorted by citations
Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review.
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“Females outperformed males on interpersonal prediction tasks (Lacroix et al., 2021).”
- Authors
- Lacroix, A., Nalborczyk, L., Dutheil, F., Kovarski, K., Chokron, S., Garrido, M., Gomot, M., & Mermillod, M.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Australian Research Council (AU)
- Université de Tours (FR)
- Corresponding author
- Lacroix, Adeline
- ORCID
- Venue
- Brain and Cognition
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 155
- Pages
- 105811
- ISSN
- 0278-2626 (ISSN-L)
- OpenAlex
- W3211217727
- Cited by
- 12
- References
- 126
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 3 · 2023: 1 · 2022: 4
- FWCI
- 1.05
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 332 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Brain and Cognition (acceptedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by-nc)
- HAL (submittedVersion)
- Funders
- Agence Nationale de la Recherche (ANR-19-P3IA-0003, ANR‐19, 10-EQPX-29-01, ANR-10-EQPX-29-01, ANR-10, ANR-10-EQPX)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- autism spectrum disorder, facial emotion recognition, high spatial frequency, low spatial frequency, spatial frequency filtering, emotional Stroop task, predictive processing, non-decision time, angry faces, low-level vision
- MeSH terms
- Facial Recognition, Adult, Autistic Disorder, Emotions, Happiness, Humans, Pattern Recognition, Visual, Photic Stimulation, Recognition, Psychology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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