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. 2025 Oct 8;19:1682603. doi: 10.3389/fnins.2025.1682603

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Copyright © 2025 Chen, Cai, Tan, Lv, Zhang and Du.

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) and the copyright owner(s) 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.

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Diagram depicting a neural network architecture featuring channel and spatial attention mechanisms. The channel attention block processes input through MaxPool, AvgPool, MLP, and Sigmoid layers before element-wise multiplication and concatenation. The spatial attention block further processes using convolution, permutation, and element-wise operations to produce the output. Various operations, such as convolution and pooling, are highlighted throughout the diagram. — SMWA block.