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Record W3117843866 · doi:10.1186/s13229-021-00435-9

Tactile cortical responses and association with tactile reactivity in young children on the autism spectrum

2021· article· en· W3117843866 on OpenAlexafffund
Svenja Espenhahn, Kate Godfrey, Sakshi Kaur, Maia Ross, Niloy Nath, Olesya Dmitrieva, Carly A. McMorris, Filomeno Cortese, Charlene Wright, Kara Murias, Deborah Dewey, Andrea B. Protzner, Adam W. McCrimmon, Signe Bray, Ashley D. Harris

Bibliographic record

VenueMolecular Autism · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHotchkiss Brain InstituteAlberta Children's HospitalUniversity of Calgary
FundersMathison Centre for Mental Health Research and EducationAlberta Children's Hospital Research InstituteCanadian Open Neuroscience PlatformUniversity of CalgaryAlberta InnovatesSick Kids FoundationNatural Sciences and Engineering Research Council of CanadaHotchkiss Brain Institute, University of Calgary
KeywordsAutismNeurotypicalSensory stimulation therapySomatosensory systemPsychologyAudiologySensory processingAutism spectrum disorderElectroencephalographySensory systemNeuropsychologyTactile discriminationCognitionNeuroscienceDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Unusual behavioral reactions to sensory stimuli are frequently reported in individuals on the autism spectrum (AS). Despite the early emergence of sensory features (< age 3) and their potential impact on development and quality of life, little is known about the neural mechanisms underlying sensory reactivity in early childhood autism. METHODS: Here, we used electroencephalography (EEG) to investigate tactile cortical processing in young children aged 3-6 years with autism and in neurotypical (NT) children. Scalp EEG was recorded from 33 children with autism, including those with low cognitive and/or verbal abilities, and 45 age- and sex-matched NT children during passive tactile fingertip stimulation. We compared properties of early and later somatosensory-evoked potentials (SEPs) and their adaptation with repetitive stimulation between autistic and NT children and assessed whether these neural measures are linked to "real-world" parent-reported tactile reactivity. RESULTS: As expected, we found elevated tactile reactivity in children on the autism spectrum. Our findings indicated no differences in amplitude or latency of early and mid-latency somatosensory-evoked potentials (P50, N80, P100), nor adaptation between autistic and NT children. However, latency of later processing of tactile information (N140) was shorter in young children with autism compared to NT children, suggesting faster processing speed in young autistic children. Further, correlational analyses and exploratory analyses using tactile reactivity as a grouping variable found that enhanced early neural responses were associated with greater tactile reactivity in autism. LIMITATIONS: The relatively small sample size and the inclusion of a broad range of autistic children (e.g., with low cognitive and/or verbal abilities) may have limited our power to detect subtle group differences and associations. Hence, replications are needed to verify these results. CONCLUSIONS: Our findings suggest that electrophysiological somatosensory cortex processing measures may be indices of "real-world" tactile reactivity in early childhood autism. Together, these findings advance our understanding of the neurophysiological mechanisms underlying tactile reactivity in early childhood autism and, in the clinical context, may have therapeutic implications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.260
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2021
Admission routes2
Has abstractyes

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