ORIGINAL RESEARCH article
Front. Psychiatry
Sec. Autism
Cortical Hemodynamic Responses and Deep Learning Models of Emotional Face Processing in Preschool Children with Autism Spectrum Disorder: A fNIRS Study
Provisionally accepted
- 1Dalian University of Technology, Dalian, China
- 2Qu Zhou College, Qu Zhou, China
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Purpose: The purpose of the present study was to characterize cortical hemodynamic responses during emotional face processing in preschool children with autism spectrum disorder (ASD) using functional near-infrared spectroscopy (fNIRS), and to develop machine learning frameworks for emotion recognition based on these hemodynamic signals. Methods: Fifty-three ASD preschoolers (41 males, 12 females; aged 3–7 years, mean age 5.20 ± 1.23 years) were exposed to dynamic video and static image facial stimuli displaying angry, happy expressions, and neutral flowers, with their brain activity concurrently recorded using whole-brain fNIRS. A convolutional neural network-long short-term memory (CNN-LSTM) model was proposed to decode spatiotemporal neural patterns of angry/happy emotion recognition. Results: fNIRS analysis revealed significantly enhanced activation in bilateral dorsolateral prefrontal cortex (DLPFC) and frontal pole during dynamic versus static stimulus processing. Angry expressions elicited the most pronounced neural responses, engaging a distributed cortical areas involving DLPFC, ventrolateral prefrontal cortex, and primary visual areas. The CNN-LSTM architecture achieved 86.2% accuracy in dynamic angry/happy emotion classification. Conclusion:This study provides evidence of altered cortical hemodynamics during dynamic emotional facial processing and demostrates the feasibility of CNN-LSTM models for the objective assessment of emotional facial processing potential in preschool children with ASD.
Keywords: Preschool children, Autism Spectrum Disorder, functional near-infrared spectroscopy (fNIRS), cerebral hemodynamic response, convolutional neural network-long short-term memory model
Received: 11 Sep 2025; Accepted: 01 Dec 2025.
Copyright: © 2025 Qi, Ni, Dong, Sun and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Liping Qi
Jian-Wei Zhang
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