ArticleCommunications biology2026
E/I imbalance and internal noise cause weak neural representations and face recognition challenges in ASD.
Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Individuals with Autism Spectrum Disorder (ASD) are known for their socio-communicative challenges, including face recognition. It is unclear, however, about its neurocomputational basis and links to neurobiological factors, such as an imbalance of excitatory and inhibitory signals (E/I imbalance) or excessive internal noise (IN). This study employed Convolutional Neural Network (CNN) models to simulate face recognition in typical populations and ASD based on the claims of E/I imbalance and IN theories. We demonstrated that CNN models with non-optimal ReLU slopes or noisy activations yielded poorer performance in face recognition and exhibited atypical neural representations of faces. Overall, simulations based on the E/I imbalance theory seem to encompass a broader range of behavioral and neural profiles in ASD. Our theory-driven approach used CNN models to test neurobiological theories, and our results provide causal evidence on a potential mechanism by which neurobiological factors influence face recognition in ASD.
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